I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
pu
t
er
E
ng
ineering
(
I
J
E
CE
)
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
,
p
p
.
1
2
1
8
~
1
2
2
8
I
SS
N:
2088
-
8
7
0
8
,
DOI
: 1
0
.
1
1
5
9
1
/ijece.
v
15
i
1
.
pp
1
2
1
8
-
1
2
2
8
1218
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ec
e.
ia
esco
r
e.
co
m
Predic
tive mo
deli
ng
f
o
r health
ca
re
wo
rker we
ll
-
bei
n
g
wit
h
clo
ud com
puting
a
nd ma
chine lear
ning
f
o
r str
ess
ma
na
g
ement
M
uthuk
a
t
ha
n Ra
j
endra
n Su
dh
a
1
,
G
na
na
m
uthu Ba
i H
em
a
M
a
lin
i
2
,
Ra
ng
a
s
a
m
y
Sa
nk
a
r
3
,
M
urug
a
a
bo
o
pa
t
hy
M
y
t
hil
y
4
,
P
is
k
a
la
Sa
t
hiy
a
m
urt
hy
K
u
m
a
re
s
h
5
,
M
a
g
esh
k
um
a
r
Na
a
ra
y
a
na
s
a
m
y
Va
r
a
da
ra
j
a
n
6
,
Sh
a
nm
ug
a
m
Su
j
a
t
ha
7
1
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
A
p
p
l
i
c
a
t
i
o
n
s,
C
o
l
l
e
g
e
o
f
S
c
i
e
n
c
e
a
n
d
H
u
m
a
n
i
t
i
e
s
,
S
R
M
I
n
st
i
t
u
t
e
o
f
S
c
i
e
n
c
e
a
n
d
Te
c
h
n
o
l
o
g
y
,
C
h
e
n
n
a
i
,
I
n
d
i
a
2
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
S
h
r
i
mat
h
i
D
e
v
k
u
n
v
a
r
N
a
n
a
l
a
l
B
h
a
t
t
V
a
i
sh
n
a
v
C
o
l
l
e
g
e
f
o
r
W
o
m
e
n
,
C
h
e
n
n
a
i
,
I
n
d
i
a
3
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
El
e
c
t
r
o
n
i
c
s E
n
g
i
n
e
e
r
i
n
g
,
C
h
e
n
n
a
i
I
n
st
i
t
u
t
e
o
f
Te
c
h
n
o
l
o
g
y
,
C
h
e
n
n
a
i
,
I
n
d
i
a
4
D
i
v
i
si
o
n
o
f
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
r
i
n
g
,
K
a
r
u
n
y
a
I
n
st
i
t
u
t
e
o
f
T
e
c
h
n
o
l
o
g
y
a
n
d
S
c
i
e
n
c
e
s,
C
o
i
m
b
a
t
o
r
e
,
I
n
d
i
a
5
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
o
n
i
c
s a
n
d
C
o
m
mu
n
i
c
a
t
i
o
n
En
g
i
n
e
e
r
i
n
g
,
K
.
L.
N
.
C
o
l
l
e
g
e
o
f
E
n
g
i
n
e
e
r
i
n
g
,
S
i
v
a
g
a
n
g
a
i
,
I
n
d
i
a
6
Le
a
d
S
o
f
t
w
a
r
e
E
n
g
i
n
e
e
r
,
G
l
e
n
A
l
l
e
n
,
U
S
A
7
D
e
p
a
r
t
me
n
t
o
f
B
i
o
m
e
d
i
c
a
l
E
n
g
i
n
e
e
r
i
n
g
,
S
a
v
e
e
t
h
a
S
c
h
o
o
l
o
f
E
n
g
i
n
e
e
r
i
n
g
,
S
a
v
e
e
t
h
a
I
n
st
i
t
u
t
e
o
f
M
e
d
i
c
a
l
a
n
d
Te
c
h
n
i
c
a
l
S
c
i
e
n
c
e
s
,
S
a
v
e
e
t
h
a
U
n
i
v
e
r
si
t
y
,
C
h
e
n
n
a
i
,
I
n
d
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
J
u
n
1
5
,
2
0
2
4
R
ev
is
ed
Sep
6
,
2
0
2
4
Acc
ep
ted
Oct
1
,
2
0
2
4
Th
is
p
a
p
e
r
p
ro
v
id
e
s
a
n
e
w
m
e
th
o
d
fo
r
stre
ss
m
a
n
a
g
e
m
e
n
t
-
fo
c
u
se
d
p
re
d
ictiv
e
m
o
d
e
li
n
g
o
f
h
e
a
lt
h
c
a
re
wo
rk
e
r
s'
we
ll
-
b
e
in
g
v
ia
c
l
o
u
d
c
o
m
p
u
ti
n
g
a
n
d
m
a
c
h
in
e
lea
rn
in
g
.
Th
e
n
e
e
d
f
o
r
p
r
o
a
c
ti
v
e
m
e
a
su
re
s
to
trac
k
a
n
d
a
ss
ist
h
e
a
lt
h
c
a
re
wo
rk
e
rs'
m
e
n
tal
h
e
a
lt
h
is
h
ig
h
li
g
h
te
d
b
y
th
e
risin
g
e
x
p
e
c
tatio
n
s
p
lac
e
d
o
n
th
e
m
.
Us
in
g
v
a
rio
u
s
d
a
ta
so
u
rc
e
s,
o
u
r
s
y
ste
m
c
o
m
p
il
e
s
in
fo
rm
a
ti
o
n
fr
o
m
su
r
v
e
y
s,
s
o
c
i
a
l
m
e
d
ia,
e
lec
tro
n
ic
h
e
a
lt
h
re
c
o
rd
s,
a
n
d
we
a
ra
b
le
d
e
v
ice
s
in
to
a
sin
g
le
lo
c
a
ti
o
n
fo
r
a
n
a
ly
sis.
P
re
d
ictiv
e
m
o
d
e
ls
th
a
t
p
re
d
ict
h
e
a
lt
h
c
a
re
wo
rk
e
rs'
stre
ss
lev
e
ls
a
n
d
we
ll
-
b
e
i
n
g
a
re
d
e
v
e
l
o
p
e
d
u
sin
g
g
ra
d
ien
t
b
o
o
st
in
g
,
a
str
o
n
g
m
a
c
h
in
e
lea
rn
i
n
g
(M
L)
tec
h
n
i
q
u
e
.
Th
i
s
wo
rk
is
su
it
a
b
le
fo
r
g
ra
d
ien
t
b
o
o
sti
n
g
d
u
e
to
it
s
re
sili
e
n
c
e
to
o
v
e
rfit
ti
n
g
a
n
d
c
a
p
a
c
it
y
to
p
r
o
c
e
ss
m
a
n
y
k
i
n
d
s
o
f
d
a
ta.
He
a
lt
h
c
a
re
o
rg
a
n
iza
ti
o
n
s
m
a
y
i
m
p
ro
v
e
t
h
e
h
e
a
lt
h
o
f
th
e
ir
e
m
p
lo
y
e
e
s
b
y
u
si
n
g
o
u
r
tec
h
n
o
lo
g
y
t
o
d
e
tec
t
stre
ss
p
a
tt
e
rn
s
a
n
d
id
e
n
t
ify
t
h
e
c
a
u
se
s
o
f
t
h
a
t
stre
ss
.
It
c
a
n
u
se
sp
e
c
ifi
c
trea
t
m
e
n
ts
a
n
d
su
p
p
o
rt
sy
ste
m
s
to
a
ll
e
v
iate
th
a
t
stre
ss
.
Wi
d
e
sp
re
a
d
a
d
o
p
ti
o
n
a
n
d
re
a
l
-
ti
m
e
m
o
n
it
o
r
in
g
a
re
m
a
d
e
p
o
ss
i
b
le
b
y
th
e
sc
a
lab
il
it
y
,
flex
i
b
il
it
y
,
a
n
d
a
c
c
e
ss
ib
il
it
y
o
f
c
lo
u
d
c
o
m
p
u
ti
n
g
in
fra
str
u
c
tu
re
.
Th
is
m
e
th
o
d
sh
o
ws
p
ro
m
i
se
in
th
e
d
irec
ti
o
n
o
f
p
r
o
a
c
ti
v
e
so
l
u
ti
o
n
s
d
riv
e
n
b
y
d
a
ta
fo
r
c
o
n
tro
l
li
n
g
th
e
stre
ss
o
f
h
e
a
lt
h
c
a
re
wo
rk
e
rs an
d
imp
r
o
v
i
n
g
th
e
ir
g
e
n
e
ra
l
we
ll
-
b
e
i
n
g
.
K
ey
w
o
r
d
s
:
C
lo
u
d
co
m
p
u
tin
g
Ma
ch
in
e
lear
n
in
g
Me
n
tal
h
ea
lth
Ph
y
s
io
lo
g
ical
d
ata
Stre
s
s
m
an
ag
em
en
t
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Mu
th
u
k
ath
a
n
R
ajen
d
r
an
Su
d
h
a
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
A
p
p
licatio
n
s
,
C
o
lleg
e
o
f
Scien
ce
a
n
d
Hu
m
an
ities
,
SR
M
I
n
s
titu
te
o
f
Scien
ce
an
d
T
ec
h
n
o
lo
g
y
Po
th
er
i,
SR
M
Nag
ar
,
Kattan
k
u
lath
u
r
,
T
a
m
il Na
d
u
6
0
3
2
0
3
,
I
n
d
ia
E
m
ail:
m
r
s
u
d
h
a5
1
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
th
e
co
r
o
n
av
ir
u
s
d
is
ea
s
e
2
0
1
9
(
C
OVI
D
-
19
)
ep
id
em
ic,
n
u
r
s
es
ar
e
s
tr
ess
ed
.
Ov
er
tim
e,
th
is
tr
em
en
d
o
u
s
p
r
ess
u
r
e
af
f
ec
ts
th
eir
h
ea
lth
,
q
u
ality
o
f
life
,
a
n
d
p
atien
t
ca
r
e.
R
ea
l
-
tim
e
s
tr
ess
d
etec
tio
n
an
d
m
o
n
ito
r
in
g
ar
e
cr
u
cial
f
o
r
ea
r
l
y
s
tr
ess
p
atter
n
d
ia
g
n
o
s
is
,
b
u
r
n
o
u
t
a
v
o
id
an
ce
,
an
d
b
etter
p
at
ien
t
-
ca
r
e
o
u
tco
m
es
in
h
ea
lth
ca
r
e
p
e
r
s
o
n
n
el
[
1
]
.
Ou
r
p
r
o
o
f
-
of
-
co
n
ce
p
t
ca
s
e
s
t
u
d
y
u
s
es
m
ac
h
in
e
lear
n
in
g
(
ML
)
an
d
ar
tific
ial
in
tellig
en
ce
(
AI
)
to
esti
m
ate
u
s
er
s
tr
ess
lev
els
b
ased
o
n
h
ea
r
t
r
ate,
v
ar
iab
ilit
y
,
a
n
d
p
h
y
s
ical
ac
tiv
ity
.
T
h
is
r
esear
ch
ex
p
lo
r
es
N
o
r
weg
ian
h
o
s
p
ital
w
o
r
k
er
s
'
s
tr
ess
an
d
cy
b
e
r
s
ec
u
r
ity
ac
tiv
ities
.
H
o
s
p
ital
d
ata
is
m
o
r
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
r
ed
ictive
mo
d
elin
g
fo
r
h
ea
lth
ca
r
e
w
o
r
ke
r
w
e
ll
-
b
ein
g
w
ith
clo
u
d
…
(
Mu
t
h
u
ka
th
a
n
R
a
jen
d
r
a
n
S
u
d
h
a
)
1219
s
u
s
ce
p
tib
le
to
cy
b
er
ass
au
lts
as
th
e
h
ea
lth
ca
r
e
in
d
u
s
tr
y
lev
er
ag
es
tech
n
o
lo
g
y
to
en
h
an
ce
p
atien
t
ca
r
e,
an
d
h
ac
k
er
s
m
ay
ex
p
lo
it
th
e
h
u
m
an
co
m
p
o
n
en
t
[
2
]
.
I
n
I
n
d
ia,
th
e
s
ec
o
n
d
C
OVI
D
-
1
9
ep
id
e
m
ic
h
as
ca
u
s
ed
d
r
u
g
s
ca
r
city
an
d
in
cr
ea
s
ed
m
o
r
b
id
ity
.
Du
e
to
th
e
e
p
id
em
ic'
s
s
u
f
f
er
in
g
,
m
o
r
tality
,
a
n
d
s
ec
lu
s
io
n
,
C
OVI
D
-
1
9
h
as
also
af
f
ec
ted
h
ea
lth
p
r
ac
titi
o
n
er
s
'
m
en
tal
h
ea
lth
[
3
]
.
T
h
is
cr
o
s
s
-
s
ec
tio
n
al
r
esear
ch
ex
am
in
es
I
n
d
ian
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als'
m
en
tal
h
ea
lth
d
u
r
in
g
t
h
e
s
ec
o
n
d
C
OVI
D
-
1
9
p
an
d
em
ic.
I
t
ad
d
r
ess
ed
th
e
s
ig
n
if
ican
t
in
ter
-
in
d
iv
id
u
al
v
a
r
iab
ilit
y
in
am
b
u
lato
r
y
b
eh
av
i
o
r
al
d
ata
b
y
d
esig
n
in
g
g
r
o
u
p
-
s
p
ec
if
ic
m
o
d
els
o
f
h
u
m
a
n
o
u
tco
m
es
[
4
]
.
Ho
s
p
ital
s
taf
f
h
ad
em
o
tio
n
al
an
d
p
s
y
ch
o
lo
g
ical
d
if
f
icu
lt
ies
af
ter
th
e
ep
id
em
ic,
wh
ich
m
ig
h
t
h
av
e
af
f
ec
ted
th
eir
m
en
tal
h
ea
lth
[
5
]
.
M
o
r
p
h
o
lo
g
ical
p
r
o
p
er
ties
o
f
p
h
o
to
p
leth
y
s
m
o
g
r
ap
h
y
(
PP
G)
wav
ef
o
r
m
s
ar
e
ex
am
i
n
ed
to
d
eter
m
in
e
C
OVI
D
-
19
-
r
elate
d
s
tr
ess
an
d
d
ep
r
ess
io
n
i
n
f
i
r
s
t
-
lin
e
h
ea
lth
ca
r
e
p
er
s
o
n
n
el.
S
tr
ess
an
d
d
e
p
r
ess
io
n
ar
e
m
o
d
estl
y
lin
k
ed
with
s
ig
n
i
f
ican
t
s
y
s
to
lic
am
p
litu
d
e
an
d
e
ar
ly
wav
e
r
ef
lectio
n
ch
ar
ac
ter
i
s
tics
.
T
h
is
m
eth
o
d
u
s
es
ap
p
r
o
ac
h
es
t
o
n
atu
r
al
l
an
g
u
ag
e
p
r
o
ce
s
s
in
g
(
NL
P)
a
n
d
ar
tific
ial
in
tellig
en
ce
(
AI
)
[
6
]
.
Dr
o
wsi
n
ess
d
etec
tio
n
an
d
p
r
ev
e
n
tio
n
ar
e
an
ef
f
ec
tiv
e
way
to
en
h
an
ce
h
o
s
p
ital
wo
r
k
er
s
af
ety
.
S
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
SVM)
ar
e
u
s
ed
to
an
ticip
ate
u
tili
zin
g
h
o
s
p
ital
d
ep
lo
y
e
d
in
t
er
n
et
of
th
in
g
s
(
I
o
T
)
in
f
r
astru
ctu
r
e
d
ata
[
7
]
.
I
o
T
in
f
r
astru
ctu
r
e
co
llects
r
ea
l
-
ti
m
e
d
ata
o
n
a
m
b
ien
t
elem
en
ts
,
wo
r
k
p
atter
n
s
,
an
d
em
p
l
o
y
ee
p
h
y
s
io
lo
g
ical
in
d
icato
r
s
.
SVM
m
o
d
els
ar
e
tr
ain
ed
o
n
lar
g
e
d
atasets
to
d
is
co
v
er
s
leep
y
p
atter
n
s
.
Nex
t,
th
e
m
o
d
el
will
b
e
u
s
ed
in
a
h
o
s
p
ital
co
n
te
x
t
to
i
d
en
tify
tire
d
n
ess
an
d
in
te
r
v
en
e
q
u
ick
ly
.
T
o
ev
alu
ate
th
e
m
e
d
iatin
g
im
p
ac
t o
f
jo
b
s
atis
f
ac
tio
n
an
d
p
r
esen
ter
s
o
n
th
e
lin
k
b
etwe
en
wo
r
k
-
r
elate
d
s
tr
ess
an
d
tu
r
n
o
v
er
in
te
n
tio
n
in
p
r
im
a
r
y
h
ea
lth
ca
r
e
p
er
s
o
n
n
el
[
8
]
.
T
h
e
well
-
b
ein
g
a
n
d
h
ea
lth
o
f
h
ea
lth
ca
r
e
wo
r
k
er
s
d
ir
ec
tly
a
f
f
ec
t
th
e
q
u
ality
o
f
tr
ea
tm
e
n
t
f
o
r
p
atien
ts
.
Hea
lth
ca
r
e
o
r
g
an
izatio
n
s
o
f
t
en
f
ail
to
h
an
d
le
em
p
lo
y
ee
b
u
r
n
o
u
t
an
d
s
tr
ess
ad
eq
u
a
tely
.
R
ea
ctiv
e
an
d
im
p
er
s
o
n
al,
tr
ad
itio
n
al
m
et
h
o
d
s
o
f
h
ea
lth
ca
r
e
wo
r
k
er
s
tr
ess
m
an
ag
em
en
t
f
all
s
h
o
r
t.
T
h
is
in
itiativ
e
in
ten
d
s
to
tr
an
s
f
o
r
m
h
ea
lth
ca
r
e
s
tr
ess
m
an
ag
em
en
t
b
y
cr
ea
tin
g
a
p
r
o
ac
tiv
e
an
d
d
ata
-
d
r
iv
en
s
y
s
tem
.
T
h
e
s
y
s
tem
will
f
o
r
ec
ast
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als
'
s
tr
e
s
s
lev
el
s
b
y
an
aly
zin
g
d
ata
f
r
o
m
s
ev
er
al
s
o
u
r
ce
s
,
in
clu
d
in
g
elec
tr
o
n
ic
h
ea
lth
r
ec
o
r
d
s
(
E
HR
s
)
an
d
wea
r
ab
le
d
ev
ices,
an
d
t
h
en
u
s
in
g
clo
u
d
c
o
m
p
u
tin
g
an
d
m
ac
h
in
e
lear
n
in
g
.
R
ec
o
g
n
izin
g
an
d
m
a
k
in
g
s
en
s
e
o
f
th
e
m
an
y
elem
en
ts
im
p
a
ctin
g
h
ea
lth
i
n
s
u
ch
a
co
m
p
licated
s
ettin
g
is
th
e
r
ea
l
p
r
o
b
lem
.
T
h
is
ap
p
r
o
ac
h
aim
s
to
in
cr
ea
s
e
r
esil
ien
ce
,
wo
r
k
h
e
alth
,
an
d
ca
r
e
d
eliv
e
r
y
b
y
o
f
f
er
in
g
ea
r
ly
in
s
ig
h
ts
an
d
p
er
s
o
n
alize
d
tr
ea
t
m
en
ts
.
T
h
e
r
esear
ch
p
r
o
p
o
s
es
u
s
in
g
clo
u
d
co
m
p
u
ti
n
g
an
d
ML
t
o
r
ed
u
ce
h
ea
lth
ca
r
e
wo
r
k
er
s
tr
ess
.
T
h
is
n
o
v
el
s
tr
ess
m
an
ag
e
m
en
t
s
tr
at
eg
y
is
p
r
o
ac
tiv
e
a
n
d
d
ata
-
d
r
iv
en
,
u
n
lik
e
r
ea
ctiv
e
m
eth
o
d
s
.
I
t
ad
v
an
ce
s
th
e
f
ield
b
y
in
teg
r
atin
g
elec
tr
o
n
ic
h
e
alth
r
ec
o
r
d
s
,
q
u
esti
o
n
n
air
es,
wea
r
ab
le
d
ev
ices,
an
d
s
o
ci
al
m
ed
ia
d
ata.
B
y
ce
n
tr
alizin
g
d
if
f
er
e
n
t
s
o
u
r
ce
s
,
th
e
s
y
s
tem
g
iv
es
a
co
m
p
lete
p
ictu
r
e
o
f
h
ea
lth
ca
r
e
wo
r
k
er
well
-
b
ein
g
,
en
ab
lin
g
m
o
r
e
ac
cu
r
ate
f
o
r
ec
asts
an
d
f
o
cu
s
ed
in
ter
v
e
n
tio
n
s
.
I
t
u
s
es
g
r
ad
ien
t
b
o
o
s
tin
g
to
s
h
o
w
h
o
w
ad
v
an
ce
d
ML
ca
n
p
r
ed
ict
h
ea
lth
ca
r
e
wo
r
k
er
s
tr
ess
.
T
h
is
alg
o
r
ith
m
ca
n
h
a
n
d
le
v
ar
ied
d
ata
s
o
u
r
ce
s
an
d
r
esis
t
o
v
er
f
itti
n
g
,
m
ak
in
g
it
id
ea
l
f
o
r
m
o
d
elin
g
h
ea
lth
ca
r
e
well
-
b
ein
g
.
I
t
ad
v
an
ce
s
p
r
e
d
ictio
n
m
o
d
els
f
o
r
h
ea
lth
ca
r
e
wo
r
k
er
well
-
b
ei
n
g
,
allo
win
g
ea
r
ly
s
tr
ess
o
r
d
iag
n
o
s
is
an
d
p
r
o
ac
tiv
e
m
an
ag
em
en
t
.
T
h
ese
alg
o
r
ith
m
s
p
r
ed
ict
s
tr
ess
an
d
r
ev
ea
l
well
-
b
ein
g
i
n
d
icato
r
s
,
e
n
ab
lin
g
h
ea
lth
ca
r
e
o
r
g
an
izatio
n
s
t
o
g
i
v
e
p
er
s
o
n
alize
d
h
elp
.
I
t
p
r
o
m
o
te
s
d
ata
-
d
r
iv
e
n
s
tr
ess
m
an
ag
em
en
t
a
p
p
r
o
ac
h
es
f
o
r
h
ea
lth
ca
r
e
wo
r
k
er
s
.
T
h
e
tech
n
o
lo
g
y
p
r
o
v
id
es
r
ea
l
-
ti
m
e
an
aly
tics
an
d
p
er
s
o
n
alize
d
h
el
p
to
q
u
ick
ly
i
m
p
r
o
v
e
th
e
wo
r
k
p
lace
f
o
r
h
ea
l
th
ca
r
e
s
taf
f
an
d
p
atien
ts
.
W
o
r
k
p
lace
s
tr
ess
in
cr
ea
s
es
b
u
r
n
o
u
t
an
d
lo
wer
s
p
atien
t
ca
r
e
in
h
ea
lth
ca
r
e.
Hea
lth
ca
r
e
wo
r
k
er
s
m
u
s
t
b
e
m
o
n
ito
r
e
d
f
o
r
s
tr
ess
to
o
f
f
er
ap
p
r
o
p
r
iate
s
o
lu
tio
n
s
,
b
u
t
t
y
p
ical
s
u
r
v
ey
tech
n
i
q
u
es
m
ay
in
ter
f
er
e
with
r
ea
l
-
wo
r
ld
d
u
ties
[
9
]
.
W
ea
r
ab
les
ca
n
co
n
tin
u
ally
d
etec
t
wo
r
k
e
r
s
tr
ess
with
o
u
t
in
v
asiv
en
ess
;
h
o
wev
er
,
c
o
n
tex
t
-
s
p
ec
if
ic
b
eh
av
io
r
s
an
d
s
tr
ess
s
em
an
tics
m
ay
af
f
ec
t
p
r
ed
ictio
n
s
.
Usi
n
g
ex
is
tin
g
d
atasets
,
i
t
u
s
es
s
h
ar
ed
s
tr
es
s
r
ep
r
esen
tatio
n
s
to
id
en
tify
g
e
n
er
alize
d
s
tr
ess
in
h
ea
lth
p
r
o
f
ess
io
n
als.
Me
n
tal
h
ea
lth
is
s
u
es
s
u
ch
as
s
tr
es
s
,
b
u
r
n
o
u
t,
m
o
r
al
h
ar
m
,
d
e
p
r
ess
io
n
,
a
n
d
tr
au
m
a
ar
e
m
o
r
e
co
m
m
o
n
a
m
o
n
g
h
ea
lth
ca
r
e
p
r
o
f
es
s
io
n
als
an
d
p
r
o
v
i
d
e
a
g
en
er
al
r
ev
iew
o
f
th
is
p
r
o
b
lem
[
1
0
]
.
T
h
ese
wo
r
r
ies
ar
e
m
ad
e
wo
r
s
e
b
y
p
u
b
lic
h
ea
lth
cr
is
es,
p
ar
ticu
lar
ly
co
n
s
id
er
in
g
n
ew
s
tu
d
ies th
at
s
h
o
w
h
o
w
th
e
C
OVI
D
-
1
9
e
p
id
em
ic
h
as a
f
f
ec
ted
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als'
m
en
tal
h
ea
lth
n
e
g
ativ
ely
.
T
h
ese
r
is
k
s
to
m
e
n
tal
h
ea
lth
ar
e
in
v
esti
g
a
tin
g
th
e
b
en
e
f
its
o
f
s
elf
-
ca
r
e
p
r
ac
tices,
p
u
ttin
g
in
p
lace
in
ter
v
en
tio
n
s
s
u
p
p
o
r
ted
b
y
ev
id
e
n
ce
,
an
d
in
s
titu
tin
g
o
r
g
an
izatio
n
al
m
ea
s
u
r
es
to
s
af
eg
u
ar
d
th
e
m
en
tal
h
ea
lth
o
f
h
ea
lth
ca
r
e
wo
r
k
e
r
s
.
Hea
lth
ca
r
e
wo
r
k
er
s
en
d
u
r
e
en
o
r
m
o
u
s
ca
s
elo
ad
s
,
litt
le
i
n
f
lu
en
ce
o
v
e
r
th
e
wo
r
k
p
lace
,
lo
n
g
h
o
u
r
s
,
an
d
c
h
an
g
in
g
o
r
g
an
izatio
n
al
s
tr
u
ct
u
r
es
an
d
p
r
o
ce
s
s
es
[
1
1
]
.
T
h
e
s
e
d
is
o
r
d
er
s
ca
u
s
e
s
tr
ess
an
d
b
u
r
n
o
u
t,
wh
ich
h
a
r
m
s
p
r
o
f
ess
io
n
als
an
d
p
atien
t
ca
r
e.
T
h
e
r
e
is
a
n
ee
d
to
p
r
o
d
u
ce
cu
r
r
icu
la
th
at
p
r
o
m
o
te
clin
ician
wellb
ein
g
an
d
s
elf
-
ca
r
e.
T
h
is
ev
alu
atio
n
will
a
s
s
es
s
th
e
p
o
s
it
iv
e
ef
f
ec
ts
o
f
m
in
d
f
u
ln
ess
-
b
ased
s
tr
ess
r
ed
u
ctio
n
p
r
o
g
r
a
m
s
o
n
well
-
b
ein
g
an
d
s
tr
ess
m
an
ag
e
m
en
t
in
th
is
d
e
m
o
g
r
ap
h
ic.
Dep
r
ess
io
n
,
an
x
iety
,
s
leep
less
n
ess
,
an
d
d
is
tr
ess
wer
e
r
ep
o
r
ted
b
y
h
ea
lth
ca
r
e
p
er
s
o
n
n
el
r
ea
ctin
g
to
th
e
s
p
r
ea
d
o
f
C
OVI
D
-
1
9
at
h
ig
h
r
ates
in
th
is
s
u
r
v
ey
r
esear
c
h
o
f
C
h
in
ese
d
o
cto
r
s
an
d
n
u
r
s
es
wo
r
k
in
g
in
f
ev
er
clin
ics
o
r
war
d
s
f
o
r
C
OVI
D
-
1
9
p
atien
ts
[
1
2
]
.
Pro
tectin
g
h
ea
lth
ca
r
e
wo
r
k
er
s
is
a
to
p
p
r
io
r
ity
as
p
ar
t
o
f
p
u
b
lic
h
ea
lth
ef
f
o
r
ts
to
co
m
b
at
th
e
C
OVI
D
-
1
9
p
an
d
em
ic.
Hea
lth
ca
r
e
p
r
o
f
ess
io
n
als
ex
p
o
s
ed
to
C
OVI
D
-
1
9
,
esp
ec
ially
wo
m
en
,
n
u
r
s
es,
an
d
f
r
o
n
tlin
e
wo
r
k
er
s
,
r
eq
u
ir
e
u
r
g
en
t sp
ec
ia
lized
tr
ea
tm
en
ts
to
s
u
p
p
o
r
t th
e
ir
m
en
tal
h
ea
lth
.
Hea
lth
ca
r
e
wo
r
k
er
s
'
(
HC
W
s
)
m
en
tal
h
ea
lth
d
u
r
i
n
g
C
OVI
D
-
1
9
tr
ea
tm
en
t
s
ettin
g
s
h
as
n
o
t
b
ee
n
well
r
esear
ch
ed
in
I
n
d
ia
.
HC
W
in
Kar
n
atak
a
State,
I
n
d
ia,
is
th
e
f
o
cu
s
o
f
th
is
in
v
esti
g
atio
n
o
f
its
in
cid
en
ce
an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
1
2
1
8
-
1
2
2
8
1220
p
o
s
s
ib
le
ca
u
s
al
f
ac
to
r
s
[
1
3
]
.
Vo
lu
n
teer
h
ea
lth
ca
r
e
wo
r
k
er
s
w
h
o
p
ar
ticip
ated
in
C
OVI
D
-
1
9
tr
ain
in
g
o
n
m
en
tal
h
ea
lth
welln
ess
wer
e
ask
ed
to
f
ill
o
u
t
a
n
an
o
n
y
m
o
u
s
o
n
li
n
e
s
u
r
v
ey
.
Alo
n
g
with
s
o
cio
-
d
em
o
g
r
a
p
h
ics,
o
th
e
r
ar
ea
s
th
at
ar
e
ev
alu
ated
in
clu
d
e
o
cc
u
p
atio
n
al
tr
aits
,
is
s
u
es
c
o
n
n
ec
ted
to
C
OVI
D
-
1
9
,
an
x
ie
ty
/d
ep
r
ess
io
n
,
d
r
u
g
u
s
ag
e,
s
u
icid
ality
,
life
s
ty
le,
a
n
d
h
o
m
e
life
.
Daily
b
ad
em
o
tio
n
s
ar
e
m
an
ag
e
d
b
y
o
u
r
e
m
o
tio
n
al
h
ea
lth
ca
r
e
s
y
s
tem
,
wh
ich
u
s
es
f
ac
ial
ex
p
r
ess
io
n
r
ec
o
g
n
itio
n
to
m
ak
e
th
e
s
y
s
tem
s
m
ar
ter
an
d
g
iv
e
s
er
v
ices
d
ep
en
d
in
g
o
n
u
s
er
em
o
tio
n
s
[
1
4
]
.
Ou
r
f
ac
i
al
ex
p
r
ess
io
n
em
o
tio
n
id
en
tif
icatio
n
p
r
o
b
lem
co
n
f
u
s
es
p
o
s
itiv
e,
n
eu
tr
al,
an
d
n
eg
ativ
e
em
o
tio
n
s
,
m
ak
in
g
th
e
em
o
tio
n
al
h
ea
lth
ca
r
e
s
y
s
tem
r
elax
p
eo
p
le
ev
e
n
wh
e
n
t
h
ey
d
o
n
o
t
h
a
v
e
b
ad
f
ee
lin
g
s
.
I
t
u
s
es
elec
tr
o
ca
r
d
io
g
r
am
(
E
C
G
)
s
tr
ess
d
etec
tio
n
to
im
p
r
o
v
e
th
e
r
elax
in
g
s
er
v
i
ce
.
Stre
s
s
d
etec
tio
n
m
ay
s
o
lv
e
f
ac
ial
ex
p
r
ess
io
n
s
an
d
em
o
tio
n
r
ec
o
g
n
itio
n
m
is
u
n
d
er
s
tan
d
in
g
s
to
p
r
o
v
id
e
th
e
s
er
v
ice.
Ou
r
f
in
d
in
g
s
s
h
o
w
th
at
s
tr
ess
m
o
n
ito
r
in
g
i
m
p
r
o
v
es
th
e
em
o
tio
n
al
h
ea
lth
ca
r
e
s
y
s
tem
'
s
p
er
f
o
r
m
an
ce
.
To
s
tr
ess
m
an
ag
em
e
n
t
an
d
co
g
n
itio
n
,
in
clu
d
i
n
g
b
r
a
in
wav
e
an
aly
s
is
,
a
p
er
s
o
n
m
ay
s
ee
s
tr
ess
as
u
p
liftin
g
o
r
d
eb
ilit
atin
g
.
An
en
h
an
cin
g
attitu
d
e
r
ea
cts
to
s
tr
ess
b
etter
an
d
is
less
n
eg
ati
v
ely
af
f
ec
te
d
th
an
a
d
e
b
ilit
atin
g
m
in
d
s
et.
Stre
s
s
attitu
d
es
m
ay
b
e
c
h
an
g
e
d
b
y
e
d
u
ca
tio
n
[
1
5
]
.
I
t
ex
a
m
in
es
wh
eth
er
e
-
h
ea
lth
ca
r
e
-
b
ased
e
d
u
c
atio
n
m
ay
im
p
r
o
v
e
s
tu
d
en
ts
'
s
tr
es
s
m
en
tality
.
I
n
h
ea
lth
ca
r
e,
s
tr
ess
is
th
e
b
ig
g
est
is
s
u
e.
T
h
is
wo
r
k
b
r
ief
ly
r
ev
ie
ws
ML
alg
o
r
ith
m
s
an
d
I
o
T
f
o
r
s
tr
ess
p
r
ed
ictio
n
.
R
esear
ch
er
s
h
av
e
d
o
n
e
a
lo
t
o
f
s
tu
d
ies
o
n
s
tr
ess
p
r
ed
ictio
n
[
1
6
]
.
I
t
co
m
p
ar
es
s
u
p
p
o
r
t
v
ec
t
o
r
m
ac
h
i
n
es
(
SVM)
an
d
k
-
n
ea
r
est
n
eig
h
b
o
r
(
k
NN)
ac
cu
r
ac
y
an
d
p
er
f
o
r
m
a
n
ce
u
s
in
g
p
er
ce
iv
e
d
s
tr
ess
s
ca
le
(
PSS
)
,
E
C
G
d
eter
m
in
ed
r
esp
ir
atio
n
(
E
DR
)
,
a
n
d
E
C
G.
Mo
d
er
n
I
o
T
ML
tech
n
i
q
u
es
ar
e
co
v
er
ed
in
th
is
s
tu
d
y
.
I
d
en
tif
y
in
g
s
tr
ess
s
o
u
r
ce
s
,
s
y
m
p
to
m
s
,
an
d
ML
te
ch
n
iq
u
es h
as a
ls
o
b
ee
n
p
r
i
o
r
itized
.
Mo
d
er
n
cu
ltu
r
e
is
p
lag
u
e
d
b
y
s
tr
ess
,
wh
ich
ca
u
s
e
s
m
an
y
p
h
y
s
ical
an
d
m
en
tal
h
ea
lth
is
s
u
es.
E
f
f
ec
tiv
e
s
tr
ess
m
an
ag
em
en
t
is
ess
en
tial
as
o
u
r
liv
es
g
et
f
aster
a
n
d
m
o
r
e
in
ter
twin
ed
.
T
h
is
p
io
n
ee
r
in
g
a
p
p
r
o
ac
h
t
o
ch
allen
g
e
u
s
es
r
ea
l
-
tim
e
s
tr
ess
m
o
n
ito
r
in
g
v
ia
th
e
I
o
T
[
1
7
]
.
I
t
p
r
o
p
o
s
es
a
co
m
p
r
eh
e
n
s
iv
e
s
y
s
tem
th
at
u
s
es
I
o
T
s
en
s
o
r
s
,
p
o
wer
f
u
l
d
ata
an
aly
ti
cs,
an
d
ML
to
m
ea
s
u
r
e
an
d
m
an
ag
e
s
tr
ess
co
n
tin
u
o
u
s
ly
t
h
e
s
y
s
tem
'
s
ML
m
o
d
el
ad
ju
s
ts
it
s
elf
b
ased
o
n
u
s
er
-
s
p
ec
if
ic
s
tr
ess
p
atter
n
s
to
esti
m
ate
r
ea
l
-
tim
e
s
tr
ess
lev
els.
T
h
e
f
ee
d
b
ac
k
a
n
d
p
er
s
o
n
alize
d
a
d
v
ice
in
clu
d
e
d
ee
p
b
r
ea
th
i
n
g
e
x
er
cises
an
d
lif
esty
le
ch
an
g
es.
T
h
e
b
o
d
y
'
s
r
ea
ctio
n
to
s
tr
ess
m
a
y
af
f
ec
t
ch
r
o
n
ic
illn
ess
s
u
f
f
e
r
er
s
'
h
ea
lth
.
Alth
o
u
g
h
tim
e
-
c
o
n
s
u
m
in
g
a
n
d
lim
ited
,
s
elf
-
ass
ess
m
en
t
q
u
esti
o
n
n
air
es
r
em
ain
th
e
g
o
ld
s
tan
d
ar
d
f
o
r
s
tr
ess
ev
alu
atio
n
[
1
8
]
.
Patien
ts
m
ay
r
ejec
t
s
tr
es
s
es
tim
ate
m
o
d
els
th
at
in
v
o
lv
e
f
ac
ial
an
aly
s
is
,
s
p
ee
ch
r
ec
o
g
n
itio
n
,
t
h
er
m
o
g
r
ap
h
y
,
a
n
d
elec
tr
o
ca
r
d
io
g
r
ap
h
y
.
A
d
is
tr
ib
u
ted
c
o
m
p
u
tin
g
p
latf
o
r
m
-
b
ased
m
u
ltich
an
n
el
d
etec
tio
n
s
y
s
tem
em
p
lo
y
in
g
P
PG
s
ig
n
al
p
r
o
ce
s
s
in
g
m
eth
o
d
s
is
s
u
g
g
ested
in
t
h
is
wo
r
k
to
e
x
tr
ac
t
n
u
m
er
o
u
s
p
h
y
s
io
lo
g
ical
d
ata.
B
o
d
y
tem
p
er
a
tu
r
e
an
d
g
alv
an
ic
s
k
in
r
esp
o
n
s
e
ac
q
u
is
itio
n
wer
e
in
co
r
p
o
r
ated
f
o
r
th
e
f
u
zz
y
lo
g
ic
s
tr
ess
est
im
ate
m
o
d
el.
C
o
v
i
d
-
1
9
h
as
ag
g
r
av
ated
HC
W
m
en
tal
h
ea
lth
b
ec
a
u
s
e
o
f
an
ex
p
o
n
e
n
tial
g
r
o
wth
in
wo
r
k
lo
ad
s
an
d
s
tr
ess
.
Stu
d
ies
h
av
e
s
h
o
wn
th
at
s
tr
ess
lev
els
af
f
ec
t
h
ea
r
t
r
ate
v
ar
iab
ilit
y
(
HR
V)
[
1
9
]
.
I
t
em
p
lo
y
ed
HR
V
to
ass
ess
p
h
y
s
icia
n
s
tr
ess
f
r
o
m
th
e
ep
id
em
ic.
T
h
eir
p
er
ce
iv
ed
s
tr
ess
s
co
r
e
q
u
esti
o
n
n
air
e
a
n
s
wer
s
d
eter
m
in
ed
th
eir
elev
ate
d
s
tr
ess
lev
els.
C
lin
ician
s
r
ep
o
r
ted
s
ev
er
e
ch
r
o
n
ic
s
tr
ess
in
4
0
%
o
f
ca
s
es
an
d
m
o
d
er
ate
ch
r
o
n
ic
s
tr
ess
in
th
e
r
est.
Ou
r
d
esig
n
co
m
b
i
n
es
g
r
ap
h
ical
tech
n
o
lo
g
ical
liter
ac
y
with
im
ag
e
p
r
o
ce
s
s
in
g
to
alle
v
iate
I
T
p
r
o
f
ess
io
n
al
s
tr
ess
[
2
0
]
.
Ou
r
s
y
s
tem
im
p
r
o
v
es
o
n
o
ld
s
tr
ess
d
is
co
v
er
y
s
y
s
tem
s
th
at
tr
ied
to
av
o
id
liv
e
d
is
co
v
er
y
an
d
s
p
ec
if
ic
co
m
f
o
r
tin
g
b
y
in
clu
d
in
g
p
er
io
d
ic
wo
r
k
er
an
aly
s
is
an
d
liv
e
in
v
en
tio
n
to
id
en
tify
wo
r
k
er
s
with
p
h
y
s
ical
an
d
co
m
p
r
ess
iv
e
lo
ad
is
s
u
es
an
d
s
u
g
g
est
s
tr
ess
-
m
an
ag
em
en
t
m
eth
o
d
s
b
y
o
u
tf
itti
n
g
p
e
r
io
d
i
c
ch
ec
k
f
o
r
m
s
.
O
u
r
ap
p
r
o
ac
h
em
p
h
asizes
s
tr
ess
m
an
ag
em
en
t
to
cr
ea
te
a
s
tr
ess
-
f
r
ee
wo
r
k
p
lace
an
d
r
eliev
e
em
p
lo
y
ee
s
tr
ain
.
Stre
s
s
i
s
s
u
es
ar
e
f
r
eq
u
en
t
a
m
o
n
g
I
T
wo
r
k
e
r
s
n
o
wad
a
y
s
.
E
m
p
lo
y
ee
s
tr
ess
r
is
es
with
ch
an
g
in
g
life
s
ty
les
an
d
wo
r
k
cu
ltu
r
es
[
2
1
]
.
Desp
ite
m
an
y
s
ec
to
r
s
a
n
d
co
r
p
o
r
atio
n
s
o
f
f
er
in
g
m
en
tal
h
ea
lth
p
lan
s
t
o
im
p
r
o
v
e
wo
r
k
p
lace
cu
ltu
r
e,
t
h
e
s
itu
atio
n
is
o
u
t
o
f
co
n
tr
o
l.
I
t
u
s
es
ML
to
an
aly
ze
s
tr
ess
p
atter
n
s
in
wo
r
k
in
g
in
d
iv
id
u
als
an
d
i
d
en
tify
t
h
e
el
em
en
ts
th
at
g
r
ea
tly
in
f
lu
en
ce
s
tr
ess
lev
els.
Da
ta
f
r
o
m
th
e
m
en
tal
h
ea
lth
s
u
r
v
ey
2
0
1
7
o
f
in
f
o
r
m
atio
n
an
d
co
m
m
u
n
icatio
n
tech
n
o
lo
g
y
(
I
C
T
)
wo
r
k
er
s
was
u
s
ed
af
ter
d
ata
clea
n
in
g
an
d
p
r
ep
r
o
ce
s
s
in
g
th
e
m
o
d
el
u
s
in
g
m
ac
h
in
e
lear
n
in
g
.
I
t
co
m
p
a
r
ed
th
e
ac
cu
r
ac
y
o
f
th
e
m
o
d
e
ls
ab
o
v
e.
B
o
o
s
tin
g
was
th
e
m
o
s
t
ac
cu
r
ate
m
o
d
el.
Gen
d
er
,
f
a
m
ily
h
is
to
r
y
,
an
d
o
cc
u
p
atio
n
al
h
e
alth
b
en
e
f
its
wer
e
s
h
o
wn
to
im
p
ac
t
s
tr
ess
u
s
in
g
d
ec
is
io
n
tr
ee
s
.
T
h
ese
f
in
d
in
g
s
allo
w
co
m
p
a
n
ie
s
to
f
o
cu
s
o
n
s
tr
ess
r
ed
u
ctio
n
an
d
s
taf
f
co
m
f
o
r
t.
Mo
s
t
s
tr
ess
ed
wo
r
k
er
s
s
ay
th
eir
p
r
o
ject
m
a
n
ag
er
s
p
r
o
v
id
e
h
ef
ty
ass
ig
n
m
en
ts
with
o
u
t
a
ck
n
o
wled
g
i
n
g
th
ei
r
d
is
co
m
f
o
r
t.
T
h
is
p
r
o
ject
will
au
to
m
ate
task
allo
ca
tio
n
b
ase
d
o
n
s
tr
ess
m
ea
s
u
r
es
an
d
ex
a
m
in
e
th
e
r
elatio
n
s
h
ip
b
etwe
en
wo
r
k
lo
a
d
d
is
tr
ib
u
tio
n
an
d
wo
r
k
p
lace
s
tr
ess
[
2
2
]
.
A
v
o
ice
-
b
ased
ch
atb
o
t
to
m
ea
s
u
r
e
em
o
tio
n
s
an
d
a
g
ad
g
et
to
ch
ec
k
em
p
lo
y
ee
b
o
d
ily
m
etr
ics
ar
e
u
s
ed
to
d
et
er
m
in
e
s
tr
ess
.
I
t
tr
an
s
f
o
r
m
ed
s
p
ee
ch
an
d
b
o
d
ily
in
d
icato
r
s
f
r
o
m
em
p
lo
y
ee
s
at
wo
r
k
to
s
tr
ess
lev
els.
Desig
n
an
d
s
p
ec
if
ics
o
f
o
u
r
wea
r
a
b
le
I
o
T
s
o
lu
tio
n
f
o
r
h
ar
s
h
o
u
t
d
o
o
r
wo
r
k
p
lace
h
ea
lt
h
an
d
s
af
ety
.
Sin
ce
New
Z
ea
la
n
d
'
s
f
o
r
estry
b
u
s
in
ess
h
as
th
e
g
r
ea
test
d
ea
th
s
an
d
ac
cid
en
ts
,
co
n
ce
n
tr
ate
o
n
its
n
ee
d
s
.
C
o
n
s
u
m
er
an
d
p
r
o
f
ess
io
n
al
wea
r
ab
les
ar
e
u
n
s
u
itab
l
e
f
o
r
f
o
r
estry
[
2
3
]
.
Du
e
to
th
ei
r
r
em
o
ten
ess
an
d
r
u
g
g
e
d
n
ess
,
f
o
r
estry
wo
r
k
p
la
ce
s
ca
n
n
o
t
u
s
e
cu
r
r
en
t
n
etwo
r
k
in
g
in
f
r
astru
ctu
r
e
an
d
ca
n
n
o
t
b
e
p
er
m
an
e
n
tly
s
et
u
p
.
I
T
wo
r
k
er
s
n
o
wa
d
ay
s
o
f
ten
ex
p
er
ien
ce
s
tr
ess
.
E
m
p
lo
y
ee
s
tr
ess
in
cr
ea
s
es
wh
en
liv
es
an
d
wo
r
k
in
g
c
u
ltu
r
es
ch
an
g
e
[
2
4
]
.
T
h
is
p
r
o
ject
will
u
s
e
I
o
T
an
d
s
u
p
er
v
is
ed
lear
n
in
g
to
s
tu
d
y
em
p
lo
y
ee
s
tr
ess
.
Af
ter
d
ata
clea
n
in
g
an
d
p
r
ep
r
o
ce
s
s
in
g
,
w
e
tr
ain
ed
o
u
r
m
o
d
el
u
s
in
g
n
aï
v
e
B
ay
es,
d
ec
is
io
n
tr
ee
,
an
d
k
NN
alg
o
r
ith
m
s
.
C
o
m
p
ar
is
o
n
s
wer
e
m
ad
e
to
t
h
e
m
o
d
el'
s
ac
cu
r
ac
y
.
T
h
e
k
NN
a
lg
o
r
ith
m
was
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
r
ed
ictive
mo
d
elin
g
fo
r
h
ea
lth
ca
r
e
w
o
r
ke
r
w
e
ll
-
b
ein
g
w
ith
clo
u
d
…
(
Mu
t
h
u
ka
th
a
n
R
a
jen
d
r
a
n
S
u
d
h
a
)
1221
m
o
s
t
ac
cu
r
ate.
Usi
n
g
th
e
alg
o
r
ith
m
,
s
ig
n
if
ican
t
s
tr
ess
v
ar
iab
l
es
wer
e
r
ev
ea
le
d
.
W
ith
th
ese
in
s
ig
h
ts
,
co
m
p
a
n
ies
m
ay
r
ed
u
ce
s
tr
ess
an
d
im
p
r
o
v
e
em
p
lo
y
ee
c
o
m
f
o
r
t.
User
-
r
elev
an
t
d
ata
i
n
en
ter
tain
m
en
t,
s
o
cial
m
ed
ia,
h
ea
lth
,
e
d
u
ca
tio
n
,
tr
a
v
el,
cu
is
in
e,
a
n
d
t
o
u
r
is
m
h
as
b
ee
n
p
r
o
v
id
e
d
v
ia
r
ec
o
m
m
en
d
er
s
y
s
tem
s
[
2
5
]
.
b
ig
d
ata
an
d
I
o
T
h
av
e
q
u
ick
ly
i
n
teg
r
ated
tech
n
o
lo
g
y
in
to
o
u
r
d
aily
liv
es,
in
clu
d
in
g
s
m
ar
t
h
ea
lth
ca
r
e.
I
n
n
o
v
ati
v
e
p
er
s
o
n
alize
d
eHe
alth
an
d
m
Hea
lt
h
ap
p
licatio
n
s
h
av
e
em
er
g
ed
d
u
e
to
th
e
wid
esp
r
ea
d
p
o
p
u
lar
ity
o
f
s
m
ar
twatch
es,
wea
r
ab
le
g
ad
g
ets,
an
d
b
io
s
en
s
o
r
s
.
ML
alg
o
r
ith
m
s
ca
n
r
ea
d
wea
r
ab
le
d
ata
a
n
d
a
d
v
is
e
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als.
Stre
s
s
is
a
h
u
g
e
is
s
u
e
n
o
wad
a
y
s
.
Stre
s
s
af
f
ec
ts
al
l
ag
es
an
d
in
cr
ea
s
es
s
er
io
u
s
illn
ess
es
s
u
ch
as
h
ea
r
t
d
is
ea
s
e
an
d
d
ep
r
ess
io
n
[
2
6
]
.
Pre
v
en
tio
n
is
b
etter
th
an
cu
r
e;
th
er
ef
o
r
e,
ea
r
ly
m
en
tal
s
tr
ess
d
etec
tio
n
h
el
p
s
p
r
e
v
en
t
h
ea
r
t
attac
k
s
an
d
d
ep
r
ess
io
n
.
Stre
s
s
ca
u
s
es
ch
an
g
es
in
b
io
lo
g
ical
s
ig
n
als,
in
clu
d
in
g
h
ea
t,
elec
tr
icity
,
im
p
ed
an
ce
,
ac
o
u
s
tics
,
an
d
o
p
tics
,
wh
ich
m
ay
b
e
u
s
ed
to
ass
ess
s
tr
ess
.
T
h
is
p
ap
er
d
esig
n
s
an
d
im
p
lem
e
n
ts
an
I
o
T
s
tr
ess
d
etec
tio
n
an
d
ca
te
g
o
r
izatio
n
s
y
s
tem
.
A
wea
r
ab
le
g
ad
g
et
m
ea
s
u
r
es
p
h
y
s
io
lo
g
i
ca
l
ch
ar
ac
ter
is
tics
u
s
in
g
t
h
r
ee
s
en
s
o
r
s
:
s
k
in
c
o
n
d
u
ctan
c
e,
E
C
G,
an
d
s
k
in
tem
p
er
atu
r
e.
A
clo
u
d
s
er
v
er
r
ec
eiv
es
m
ea
s
u
r
em
en
ts
f
r
o
m
t
h
e
u
s
er
'
s
p
h
o
n
e
[
2
7
]
.
AI
s
y
s
tem
s
an
aly
ze
s
en
s
o
r
d
ata
in
th
e
clo
u
d
to
ass
ess
u
s
er
s
tr
ess
.
T
h
e
u
s
er
'
s
p
h
o
n
e
d
is
p
lay
s
th
e
ex
p
ec
ted
s
tatu
s
an
d
s
u
g
g
ests
s
tr
ess
-
r
eliev
in
g
ac
tiv
ities
.
I
n
e
m
er
g
en
cy
s
tr
ess
,
th
e
d
o
cto
r
r
ec
eiv
es
a
n
o
tific
atio
n
an
d
m
a
y
v
ie
w
th
e
d
ata
v
ia
t
h
e
clo
u
d
s
er
v
er
.
T
h
e
r
ea
l
-
tim
e
s
en
s
o
r
d
ata
-
b
ased
b
in
a
r
y
class
if
icatio
n
s
y
s
tem
ac
h
iev
es
ac
c
u
r
ac
y
.
Stre
s
s
is
an
ab
n
o
r
m
al
s
tr
ain
o
n
d
aily
liv
i
n
g
.
Stre
s
s
is
o
n
e
o
f
th
e
m
ain
ca
u
s
es
o
f
ch
r
o
n
ic
h
ea
lth
d
is
ea
s
es.
T
h
u
s
,
s
tr
ess
m
an
ag
em
en
t
is
cr
u
cial
in
t
h
is
ag
e
[
2
8
]
.
I
t
d
is
cu
s
s
es
s
tr
ess
d
etec
tio
n
m
eth
o
d
s
th
at
em
p
lo
y
lo
w
-
co
s
t
wea
r
a
b
le
s
en
s
o
r
s
an
d
ML
alg
o
r
ith
m
s
[
2
9
]
to
p
r
ed
ict
s
tr
ess
lev
els.
2.
P
RO
P
O
SE
D
M
E
T
H
O
D
Mo
n
ito
r
in
g
t
h
e
h
ea
lth
o
f
th
ese
ess
en
tial
f
r
o
n
tlin
e
wo
r
k
er
s
is
o
f
th
e
u
tm
o
s
t
im
p
o
r
tan
ce
in
th
e
m
o
d
er
n
h
ea
lth
ca
r
e
s
y
s
tem
,
wh
er
e
th
e
d
em
an
d
s
p
lace
d
o
n
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als ar
e
co
n
s
tan
tly
r
i
s
in
g
.
An
in
n
o
v
ativ
e
m
eth
o
d
th
at
u
tili
ze
s
clo
u
d
co
m
p
u
tin
g
,
g
r
a
d
ien
t
b
o
o
s
tin
g
,
an
d
p
r
ed
ictiv
e
m
o
d
elin
g
m
ig
h
t
co
m
p
letely
tr
an
s
f
o
r
m
s
tr
ess
m
an
ag
em
en
t
tactics
in
h
o
s
p
ital
s
ett
in
g
s
,
r
eso
lv
in
g
th
is
cr
u
cial
p
r
o
b
lem
.
Pre
d
ictiv
e
m
o
d
els
th
at
p
r
ed
ict
h
ea
lth
ca
r
e
wo
r
k
er
s
'
s
tr
ess
lev
els
an
d
well
-
b
ein
g
ar
e
d
e
v
elo
p
e
d
u
s
in
g
g
r
a
d
ien
t
b
o
o
s
tin
g
,
a
s
tr
o
n
g
ML
tech
n
iq
u
e.
T
h
is
wo
r
k
is
s
u
itab
le
f
o
r
g
r
ad
ie
n
t
b
o
o
s
tin
g
d
u
e
to
its
r
esil
ien
ce
to
o
v
er
f
itt
in
g
an
d
ca
p
ac
ity
to
p
r
o
ce
s
s
m
an
y
k
in
d
s
o
f
d
ata.
Hea
lth
ca
r
e
o
r
g
an
izatio
n
s
m
ay
im
p
r
o
v
e
th
e
h
ea
lth
o
f
th
eir
em
p
lo
y
ee
s
b
y
u
s
in
g
o
u
r
tech
n
o
lo
g
y
to
d
etec
t stre
s
s
p
atter
n
s
an
d
i
d
en
tify
th
e
ca
u
s
es o
f
th
at
s
tr
ess
.
2
.
1
.
Understa
nd
ing
t
he
s
y
s
t
em
a
rc
hite
ct
ure
T
h
is
s
y
s
tem
i
s
b
u
ilt
ar
o
u
n
d
a
s
o
lid
f
o
u
n
d
atio
n
o
f
d
ata
co
llected
f
r
o
m
v
ar
io
u
s
s
o
u
r
ce
s
,
in
clu
d
in
g
E
HR
,
wea
r
ab
le
d
ev
ices,
q
u
esti
o
n
n
air
es,
an
d
m
o
r
e
.
T
im
e
o
f
f
,
p
atien
t
lo
ad
s
,
s
leep
h
ab
its
,
ex
er
cise
lev
els,
s
tr
ess
lev
els,
an
d
o
th
er
v
ital
life
m
etr
ics
ar
e
all
co
v
er
ed
b
y
th
is
d
ata.
Pre
p
r
o
ce
s
s
in
g
is
f
r
eq
u
en
tly
n
ec
ess
ar
y
t
o
g
u
ar
an
tee
th
e
q
u
ality
a
n
d
tr
u
s
two
r
th
in
ess
o
f
th
is
r
aw
d
ata.
I
t
is
cr
u
cial
to
clea
n
th
e
d
ata,
d
ea
l
with
m
is
s
in
g
v
alu
es,
an
d
f
in
d
o
u
tlier
s
b
e
f
o
r
e
f
u
r
th
e
r
a
n
aly
s
is
.
T
h
e
f
ea
tu
r
e
en
g
in
ee
r
in
g
p
r
o
ce
d
u
r
e
f
o
llo
ws
th
e
d
ata
p
r
ep
r
o
ce
s
s
in
g
p
h
ase.
At
th
is
s
tag
e,
it
will
ex
tr
ac
t
u
s
ef
u
l
ch
ar
ac
ter
is
tics
f
r
o
m
th
e
d
ata
th
a
t
s
h
o
w
h
o
w
h
ap
p
y
h
ea
lth
ca
r
e
wo
r
k
er
s
ar
e.
W
o
r
k
lo
ad
m
ea
s
u
r
em
en
ts
,
s
h
if
t
p
atter
n
s
,
p
atien
t
co
n
tact
f
r
eq
u
en
cy
,
p
h
y
s
ical
ac
tiv
ity
lev
els,
s
leep
q
u
ality
,
an
d
o
th
er
p
er
tin
en
t
elem
en
ts
m
ig
h
t
b
e
in
clu
d
ed
in
th
ese
d
etails.
Dev
elo
p
i
n
g
r
eliab
le
p
r
ed
ictio
n
m
o
d
els
r
eq
u
ir
es
m
eticu
lo
u
s
atten
tio
n
to
d
etail
in
s
elec
ti
n
g
an
d
co
n
s
tr
u
ctin
g
th
ese
ch
ar
ac
ter
is
tics
.
T
h
e
g
r
ad
ien
t
-
b
o
o
s
tin
g
ad
v
a
n
ce
d
m
ac
h
in
e
lear
n
in
g
m
eth
o
d
is
a
k
ey
c
o
m
p
o
n
en
t
o
f
th
is
s
y
s
tem
'
s
p
r
ed
ictiv
e
m
o
d
elin
g
.
T
h
e
n
o
n
lin
ea
r
c
o
r
r
elatio
n
s
b
etwe
en
ch
ar
ac
ter
is
tics
an
d
o
u
tco
m
es
an
d
co
m
p
licated
,
h
ig
h
-
d
im
en
s
io
n
al
d
ata
ar
e
ef
f
ec
ti
v
ely
h
an
d
le
d
b
y
alg
o
r
ith
m
s
.
T
o
r
ed
u
ce
p
r
ed
ictio
n
er
r
o
r
s
,
g
r
ad
ien
t
b
o
o
s
tin
g
tech
n
iq
u
es
iter
ativ
ely
tr
ai
n
e
n
s
em
b
les
o
f
m
o
d
els
to
g
et
b
etter
p
r
ed
ictio
n
s
.
W
h
ile
tr
ain
i
n
g
,
v
alid
atin
g
,
a
n
d
d
ep
lo
y
in
g
m
o
d
els,
th
e
s
y
s
tem
u
s
es th
e
s
ca
lab
ilit
y
an
d
f
lex
ib
i
lity
clo
u
d
co
m
p
u
tin
g
in
f
r
astru
ctu
r
e
o
f
f
e
r
s
.
C
lo
u
d
co
m
p
u
tin
g
[
3
0
]
allo
ws
f
o
r
th
e
f
ast
p
r
o
ce
s
s
in
g
o
f
m
ass
iv
e
am
o
u
n
ts
o
f
d
ata
an
d
c
o
m
p
licated
m
ac
h
in
e
lear
n
in
g
jo
b
s
b
y
p
r
o
v
id
in
g
o
n
-
d
em
an
d
ac
ce
s
s
to
c
o
m
p
u
ter
r
eso
u
r
ce
s
.
C
lo
u
d
-
b
as
ed
s
o
lu
tio
n
s
m
a
k
e
in
teg
r
atio
n
with
p
r
ee
x
is
tin
g
h
ea
lth
ca
r
e
s
y
s
tem
s
an
d
p
r
o
ce
d
u
r
es
ea
s
ier
,
p
r
o
v
i
d
in
g
ac
ce
s
s
ib
ilit
y
an
d
ad
ap
tab
ilit
y
.
I
t
is
cr
u
cial
to
e
v
alu
ate
an
d
v
alid
ate
p
r
ed
ictio
n
m
o
d
els
th
o
r
o
u
g
h
ly
to
g
u
ar
a
n
tee
th
eir
r
eliab
ilit
y
an
d
g
en
e
r
aliza
b
ilit
y
.
Acc
u
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
a
n
d
ar
ea
u
n
d
er
th
e
c
u
r
v
e
a
r
e
m
etr
ics
u
s
ed
to
ev
alu
ate
th
e
m
o
d
el'
s
p
er
f
o
r
m
a
n
ce
.
Pre
v
en
tin
g
m
o
d
els
f
r
o
m
f
ailin
g
i
n
r
ea
l
-
wo
r
ld
h
ea
lth
ca
r
e
s
ettin
g
s
an
d
m
ak
i
n
g
g
o
o
d
g
en
er
aliza
tio
n
s
to
n
ew
d
ata
r
eq
u
ir
es
r
ig
o
r
o
u
s
v
alid
atio
n
.
T
h
e
s
y
s
tem
'
s
es
s
en
tial
s
tep
i
s
d
ep
lo
y
in
g
tr
ain
ed
m
o
d
els
in
to
p
r
o
d
u
ctio
n
s
y
s
tem
s
in
s
id
e
h
ea
lth
ca
r
e
s
ettin
g
s
.
I
n
teg
r
atin
g
with
c
u
r
r
en
t
s
y
s
tem
s
,
s
u
ch
as
E
HR
o
r
wo
r
k
f
o
r
ce
m
an
a
g
em
en
t p
latf
o
r
m
s
,
h
ea
lth
ca
r
e
wo
r
k
er
s
'
well
-
b
ein
g
m
a
y
b
e
m
o
n
ito
r
e
d
in
r
ea
l
-
tim
e.
T
h
r
o
u
g
h
th
e
s
ea
m
less
in
teg
r
atio
n
o
f
p
r
e
d
ictiv
e
m
o
d
els
in
to
h
ea
lth
ca
r
e
o
r
g
an
izatio
n
s
'
ev
er
y
d
ay
o
p
er
atio
n
s
,
s
tr
ess
es
m
ay
b
e
p
r
o
ac
tiv
ely
id
en
tifie
d
an
d
ad
d
r
e
s
s
ed
,
lead
in
g
to
h
ea
lth
ier
an
d
m
o
r
e
r
esil
ien
t
s
taf
f
.
T
h
e
s
y
s
tem
ca
n
tr
ac
k
r
ea
l
-
tim
e
m
o
d
el
p
e
r
f
o
r
m
an
ce
b
y
s
ee
k
in
g
h
o
s
p
ital
m
an
a
g
er
s
a
n
d
s
taf
f
in
p
u
t.
R
etain
in
g
m
o
d
els
r
eg
u
lar
ly
with
n
ew
d
ata
k
ee
p
s
p
r
e
d
ictio
n
m
o
d
els
cu
r
r
en
t
a
n
d
a
cc
u
r
ate.
Hea
lth
ca
r
e
co
m
p
an
ies
m
a
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
1
2
1
8
-
1
2
2
8
1222
b
etter
ad
d
r
ess
th
eir
em
p
lo
y
ee
s
'
ch
an
g
in
g
s
tr
ess
lev
els
b
y
in
s
titu
tin
g
a
cu
ltu
r
e
o
f
co
n
tin
u
o
u
s
im
p
r
o
v
em
e
n
t
an
d
ad
ju
s
tin
g
th
eir
s
tr
ess
m
an
ag
em
en
t
p
r
ac
tices
ac
co
r
d
in
g
ly
[
3
1
]
.
Fig
u
r
e
1
s
h
o
ws
h
o
w
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
u
s
es
clo
u
d
c
o
m
p
u
tin
g
t
o
f
ac
il
itate
d
ata
p
r
o
ce
s
s
in
g
,
tr
ain
i
n
g
m
o
d
els,
p
r
ed
ictio
n
,
a
n
d
an
al
y
s
is
.
T
h
is
,
in
tu
r
n
,
allo
ws f
o
r
ef
f
icien
t a
n
d
s
ca
lab
le
m
an
ag
em
en
t
o
f
h
e
alth
ca
r
e
wo
r
k
er
s
'
well
-
b
ein
g
.
Fig
u
r
e
1
.
Sy
s
tem
ar
c
h
itectu
r
e
f
o
r
p
r
o
p
o
s
ed
h
ea
lth
ca
r
e
w
o
r
k
e
r
well
-
b
ein
g
2
.
2
.
G
r
a
dient
bo
o
s
t
ing
m
o
de
l t
ra
ini
ng
pro
ce
s
s
T
h
e
s
y
s
tem
'
s
g
r
ad
ien
t b
o
o
s
tin
g
tech
n
iq
u
e
is
d
escr
ib
ed
in
f
u
r
th
er
d
etail
h
er
e:
a.
Data
p
r
ep
r
o
ce
s
s
in
g
:
P
r
ep
r
o
ce
s
s
in
g
is
u
s
ed
to
p
r
e
p
ar
e
th
e
r
aw
d
ata
f
o
r
tr
ain
in
g
m
o
d
els.
T
h
is
d
ata
c
o
m
es
f
r
o
m
s
ev
er
al
s
o
u
r
ce
s
,
in
clu
d
in
g
wea
r
ab
le
d
ev
ices
[
3
2
]
.
Am
o
n
g
th
e
r
esp
o
n
s
ib
ilit
ies
ar
e
en
co
d
in
g
ca
teg
o
r
ical
v
ar
iab
les,
m
a
n
ag
i
n
g
m
is
s
in
g
d
ata,
a
n
d
n
o
r
m
ali
zin
g
n
u
m
er
ical
ch
ar
ac
ter
is
tics
to
en
s
u
r
e
th
e
y
ar
e
o
n
th
e
s
am
e
s
ca
le.
b.
Feat
u
r
e
e
n
g
i
n
e
er
in
g
:
I
m
p
o
r
ta
n
t
p
a
tte
r
n
s
a
n
d
co
r
r
e
lati
o
n
s
a
r
e
ca
p
t
u
r
ed
b
y
e
n
g
i
n
ee
r
i
n
g
u
s
e
f
u
l
ch
ar
ac
te
r
is
ti
cs
o
n
ce
t
h
e
d
ata
is
p
r
e
p
r
o
c
ess
e
d
.
W
ea
r
ab
le
d
e
v
ice
d
ata
m
a
y
p
r
o
v
id
e
in
s
ig
h
ts
in
to
,
a
m
o
n
g
o
t
h
er
th
i
n
g
s
,
p
h
y
s
io
lo
g
ical
s
ig
n
als
(
lik
e
h
ea
r
t
r
ate
v
ar
iab
ilit
y
)
,
ac
tiv
ity
lev
els
(
lik
e
s
tep
co
u
n
t)
,
an
d
s
le
ep
p
atter
n
s
(
lik
e
len
g
th
an
d
q
u
ality
o
f
s
leep
)
.
T
o
in
cr
ea
s
e
th
e
m
o
d
el'
s
p
r
ed
icti
o
n
p
er
f
o
r
m
a
n
ce
,
f
ea
tu
r
e
en
g
in
ee
r
in
g
s
ee
k
s
to
p
r
o
v
id
e
it with
u
s
ef
u
l in
p
u
t f
e
atu
r
es.
c.
Mo
d
el
t
r
ain
in
g
:
T
h
e
p
u
r
p
o
s
e
o
f
tr
ain
in
g
a
g
r
ad
ien
t
-
b
o
o
s
ti
n
g
m
o
d
el
is
to
u
s
e
th
e
tr
ea
te
d
an
d
m
o
d
if
ied
f
ea
tu
r
es.
C
o
m
b
in
i
n
g
s
ev
e
r
al
w
ea
k
lear
n
e
r
s
,
u
s
u
ally
d
ec
is
io
n
tr
ee
s
,
in
to
a
s
in
g
le
r
o
b
u
s
t
p
r
ed
ictio
n
m
o
d
el
is
th
e
g
o
al
o
f
th
e
en
s
em
b
le
lear
n
in
g
m
eth
o
d
k
n
o
w
n
as
g
r
a
d
ien
t
b
o
o
s
tin
g
.
g
r
a
d
ien
t
b
o
o
s
tin
g
tr
ain
s
a
n
ew
d
ec
is
io
n
tr
ee
iter
ativ
ely
b
y
f
itt
in
g
it
to
th
e
r
esid
u
als
(
er
r
o
r
s
)
o
f
th
e
o
ld
tr
ee
s
.
T
h
is
iter
ativ
e
ap
p
r
o
ac
h
aim
s
to
im
p
r
o
v
e
th
e
en
s
em
b
le
m
o
d
el's
p
r
ed
icted
ac
cu
r
ac
y
b
y
r
ed
u
cin
g
th
e
m
is
tak
es
it
m
ak
es.
I
t
is
p
o
s
s
ib
le
to
f
in
e
-
tu
n
e
th
e
m
o
d
el'
s
p
er
f
o
r
m
an
ce
b
y
ad
j
u
s
tin
g
th
e
g
r
a
d
ien
t
b
o
o
s
tin
g
alg
o
r
ith
m
'
s
h
y
p
er
p
a
r
am
eter
s
,
in
clu
d
in
g
t
h
e
lear
n
in
g
r
ate,
tr
e
e
d
ep
th
,
a
n
d
to
tal
iter
atio
n
.
d.
Mo
d
el
e
v
alu
atio
n
:
Fo
llo
win
g
tr
ain
in
g
,
th
e
g
r
ad
ien
t
b
o
o
s
ti
n
g
m
o
d
el
is
ass
ess
ed
u
s
in
g
s
u
itab
le
cr
iter
ia.
Acc
u
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
F
1
-
s
co
r
e,
a
n
d
ar
ea
u
n
d
er
t
h
e
R
OC
cu
r
v
e
(
AUC
-
R
O
C
)
ar
e
c
o
m
m
o
n
m
etr
ics
f
o
r
class
if
icatio
n
task
s
.
T
o
en
s
u
r
e
th
e
m
o
d
el
ca
n
h
an
d
le
n
e
w
d
ata
an
d
is
g
en
er
aliza
b
le,
it
m
ay
b
e
test
ed
u
s
in
g
m
eth
o
d
s
lik
e
cr
o
s
s
-
v
ali
d
atio
n
.
T
h
e
m
o
d
el
ass
ess
m
en
t
is
all
ab
o
u
t
f
in
d
in
g
o
u
t
h
o
w
well
th
e
m
o
d
el
p
r
ed
icts
h
ea
lth
ca
r
e
wo
r
k
er
s
'
s
t
r
ess
lev
els an
d
,
if
n
ee
d
e
d
,
wh
e
r
e
th
ey
ca
n
b
e
im
p
r
o
v
e
d
.
e.
Mo
d
el
d
ep
lo
y
m
en
t:
T
h
e
g
r
ad
i
en
t
b
o
o
s
tin
g
m
o
d
el
is
u
s
ed
to
m
ak
e
p
r
ed
ictio
n
s
o
n
f
r
esh
d
at
a
if
it
p
er
f
o
r
m
s
well
d
u
r
in
g
ass
ess
m
en
t.
Usi
n
g
in
p
u
t
v
a
r
iab
les
lik
e
p
h
y
s
io
l
o
g
ical
d
ata
f
r
o
m
wea
r
ab
les
an
d
o
th
er
p
er
tin
en
t
cr
iter
ia,
th
e
d
ep
l
o
y
ed
m
o
d
el
m
ay
p
r
ed
ict
s
tr
ess
lev
els f
o
r
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als.
f.
Feed
b
ac
k
lo
o
p
:
Fo
r
h
ea
lth
ca
r
e
p
er
s
o
n
n
el
wh
o
h
av
e
b
ee
n
r
ec
o
g
n
ized
as
h
av
in
g
h
ig
h
lev
els
o
f
s
tr
ess
,
th
e
p
r
ed
ictio
n
s
m
ad
e
b
y
th
e
d
ep
l
o
y
ed
m
o
d
el
m
ig
h
t
g
u
id
e
tr
ea
t
m
en
ts
o
r
h
elp
.
T
h
e
g
r
ad
ien
t
b
o
o
s
tin
g
m
o
d
el
m
ay
b
e
co
n
tin
u
o
u
s
ly
im
p
r
o
v
ed
u
s
in
g
th
e
f
ee
d
b
ac
k
f
r
o
m
t
h
ese
tr
ea
tm
en
ts
an
d
f
r
esh
d
at
a
ac
q
u
ir
ed
o
v
er
tim
e.
As
h
ea
lth
ca
r
e
wo
r
k
er
s
'
h
ea
lth
an
d
s
tr
ess
lev
els
ev
o
lv
e,
th
is
f
ee
d
b
ac
k
lo
o
p
k
ee
p
s
th
e
m
o
d
el
cu
r
r
en
t
an
d
f
lex
ib
le.
T
h
e
s
y
s
tem
'
s
p
r
o
ce
s
s
is
s
h
o
wn
in
Fig
u
r
e
2
f
lo
wch
ar
t.
T
h
e
d
ata
is
f
ir
s
t
co
llected
an
d
th
en
u
n
d
er
g
o
es
p
r
ep
r
o
c
ess
in
g
an
d
f
ea
tu
r
e
en
g
i
n
ee
r
in
g
to
p
r
ep
ar
e
it
f
o
r
tr
ai
n
in
g
th
e
m
o
d
e
l.
T
h
e
m
eth
o
d
D
a
t
a
so
u
r
c
e
s
C
l
o
u
d
p
l
a
t
f
o
r
m (
s
t
o
r
a
g
e
,
c
o
m
p
u
t
i
n
g
)
D
a
t
a
p
r
o
c
e
s
si
n
g
&
p
r
e
p
ar
at
i
o
n
F
e
a
t
u
r
e
e
n
g
i
n
e
e
r
i
n
g
a
n
d
sel
e
c
t
i
o
n
M
o
d
e
l
t
r
a
i
n
i
n
g
(
G
r
ad
i
e
n
t
b
o
o
st
i
n
g
)
Fe
e
d
b
a
c
k
l
o
o
p
c
o
n
t
i
n
u
o
u
s
i
mp
r
o
v
e
me
n
t
P
r
e
d
i
c
t
i
o
n
a
n
d
a
n
a
l
y
si
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
r
ed
ictive
mo
d
elin
g
fo
r
h
ea
lth
ca
r
e
w
o
r
ke
r
w
e
ll
-
b
ein
g
w
ith
clo
u
d
…
(
Mu
t
h
u
ka
th
a
n
R
a
jen
d
r
a
n
S
u
d
h
a
)
1223
co
n
clu
d
es
with
d
ep
lo
y
i
n
g
t
h
e
tr
ain
ed
m
o
d
el
f
o
r
p
r
ed
ictio
n
s
an
d
co
n
d
u
ctin
g
p
e
r
f
o
r
m
an
ce
e
v
alu
atio
n
s
.
T
h
is
s
y
s
tem
atic
p
r
o
ce
d
u
r
e
g
u
ar
a
n
tees
th
e
ef
f
icien
t
u
s
e
o
f
d
ata
to
p
r
o
v
id
e
f
o
r
ec
asts
ab
o
u
t
th
e
h
ea
lth
o
f
h
ea
lth
ca
r
e
wo
r
k
er
s
[
3
3
]
.
Fig
u
r
e
2
.
W
o
r
k
f
lo
w
f
lo
wch
a
r
t
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Resul
t
s
T
h
e
d
e
p
lo
y
ed
s
o
lu
tio
n
u
tili
ze
s
clo
u
d
c
o
m
p
u
tin
g
a
n
d
m
a
ch
in
e
lear
n
i
n
g
t
o
ad
d
r
ess
th
e
p
r
ess
in
g
p
r
o
b
lem
o
f
h
ea
lth
ca
r
e
wo
r
k
e
r
well
-
b
ein
g
,
in
clu
d
in
g
s
tr
ess
m
an
ag
em
en
t.
T
h
e
s
y
s
tem
p
r
o
v
id
es
p
r
o
ac
tiv
e
m
eth
o
d
s
to
aid
h
ea
lt
h
ca
r
e
wo
r
k
er
s
'
m
en
tal
h
ea
lth
a
n
d
r
e
d
u
ce
s
tr
ess
v
ia
p
r
ed
ictiv
e
m
o
d
el
in
g
.
W
ea
r
ab
le
tech
an
d
AI
-
p
o
we
r
ed
alg
o
r
ith
m
s
k
ee
p
tab
s
o
n
v
ar
io
u
s
p
h
y
s
io
lo
g
ical
an
d
b
eh
av
i
o
r
al
m
ar
k
e
r
s
,
lettin
g
u
s
er
s
ca
tch
s
tr
ess
p
atter
n
s
ea
r
ly
an
d
h
elp
th
em
co
p
e
b
etter
.
T
o
esti
m
ate
th
e
s
tr
ess
lev
el
s
o
f
h
ea
lth
ca
r
e
wo
r
k
er
s
,
th
e
s
y
s
tem
'
s
p
r
ed
ictiv
e
m
o
d
elin
g
co
m
p
o
n
e
n
t
u
s
es
ex
ten
s
iv
e
d
ata
g
ath
er
ed
f
r
o
m
wea
r
ab
le
d
ev
ices
an
d
ap
p
lies
s
o
p
h
is
ticated
m
ac
h
in
e
lear
n
i
n
g
m
eth
o
d
s
s
u
ch
as
g
r
ad
ie
n
t
b
o
o
s
tin
g
.
Hea
lth
ca
r
e
b
u
s
in
ess
es
m
ay
p
r
o
tect
th
ei
r
wo
r
k
er
s
f
r
o
m
p
o
s
s
ib
le
s
tr
ess
es
b
y
u
s
in
g
t
h
is
p
r
ed
ictiv
e
s
k
ill
to
id
en
tify
th
em
ea
r
l
y
o
n
an
d
m
an
ag
e
th
em
b
ef
o
r
e
t
h
ey
g
et
w
o
r
s
e.
T
h
e
s
y
s
tem
's
ar
ch
itectu
r
e
is
b
u
ilt
o
n
clo
u
d
co
m
p
u
tin
g
,
g
u
ar
an
teein
g
s
ca
lab
ilit
y
,
d
ep
en
d
a
b
ilit
y
,
an
d
ac
ce
s
s
ib
ilit
y
.
T
h
e
s
y
s
tem
'
s
ab
ilit
y
to
an
aly
ze
an
d
s
to
r
e
d
ata
o
n
th
e
clo
u
d
allo
ws it to
m
an
ag
e
m
ass
iv
e
am
o
u
n
ts
o
f
d
ata
ef
f
ec
tiv
ely
,
m
ee
t
th
e
g
r
o
win
g
d
em
an
d
,
an
d
p
r
o
v
i
d
e
h
ea
lth
ca
r
e
co
m
p
a
n
ies
with
r
ea
l
-
tim
e
in
s
ig
h
ts
.
I
n
ad
d
itio
n
to
f
ac
ilit
atin
g
r
em
o
te
ac
ce
s
s
f
o
r
h
ea
lth
ca
r
e
wo
r
k
er
s
an
d
allo
win
g
s
ea
m
less
in
ter
ac
tio
n
with
cu
r
r
e
n
t
h
ea
lth
ca
r
e
I
T
s
y
s
tem
s
,
clo
u
d
-
b
ased
d
ep
lo
y
m
en
t
p
r
o
m
o
tes
wid
er
ac
ce
p
tan
ce
an
d
u
s
e.
T
h
e
m
eth
o
d
m
ig
h
t
s
ig
n
if
ican
tly
alter
h
ea
lth
ca
r
e
wo
r
k
er
welln
ess
p
r
o
g
r
am
s
.
Staf
f
m
o
r
ale,
p
r
o
d
u
ctiv
ity
,
an
d
p
atien
t
ca
r
e
m
ay
all
b
e
b
o
o
s
ted
w
h
en
we
tak
e
m
ea
s
u
r
es to
co
m
b
at
s
tr
ess
an
d
p
r
o
m
o
te
m
en
tal
welln
ess
.
Mo
r
eo
v
er
,
h
e
alth
ca
r
e
o
r
g
a
n
izatio
n
s
ca
n
n
o
w
m
ak
e
ev
id
en
ce
-
b
ased
d
ec
is
io
n
s
th
an
k
s
to
th
e
d
ata
-
d
r
iv
en
s
y
s
tem
.
T
h
is
allo
ws
th
em
to
cu
s
to
m
ize
tr
ea
tm
en
ts
an
d
s
u
p
p
o
r
t
m
eth
o
d
s
to
m
ee
t
th
e
s
p
ec
if
ic
r
eq
u
ir
em
e
n
ts
o
f
th
eir
s
taf
f
.
T
h
e
s
y
s
tem
is
a
h
u
g
e
s
tep
f
o
r
war
d
r
eg
ar
d
i
n
g
h
ea
lth
ca
r
e
p
e
r
s
o
n
n
el’
s
ac
ce
s
s
to
tech
n
o
lo
g
ical
r
eso
u
r
ce
s
th
at
p
r
o
m
o
te
th
eir
h
ea
lth
an
d
s
af
e
ty
.
I
t
p
r
o
v
id
es
a
n
all
-
en
c
o
m
p
ass
in
g
s
tr
ateg
y
f
o
r
s
tr
ess
m
an
ag
em
en
t
b
y
in
teg
r
at
in
g
clo
u
d
c
o
m
p
u
tin
g
with
p
r
e
d
ictiv
e
m
o
d
elin
g
ca
p
ab
ilit
ies,
lead
in
g
to
a
r
o
b
u
s
t
h
ea
lth
ca
r
e
wo
r
k
f
o
r
ce
th
at
is
b
o
th
h
ea
lth
y
a
n
d
ef
f
icien
t.
T
h
e
m
eth
o
d
m
i
g
h
t
c
h
an
g
e
th
e
liv
es
o
f
h
ea
lth
ca
r
e
p
r
o
v
id
e
r
s
an
d
th
ei
r
p
atien
ts
if
it is
r
ef
in
ed
an
d
a
d
o
p
te
d
b
y
m
an
y
.
3
.
2
.
Dis
cu
s
s
io
n
As
d
is
cu
s
s
ed
in
th
e
d
eb
ate,
p
r
o
ac
tiv
e
s
tr
ess
m
an
ag
em
e
n
t
c
an
tr
an
s
f
o
r
m
h
ea
lth
ca
r
e
wo
r
k
er
s
'
well
-
b
ein
g
.
T
h
e
s
o
lu
tio
n
e
n
ab
les
s
ca
lab
le
an
d
tailo
r
e
d
tr
ea
tm
en
ts
b
ased
o
n
d
ata
f
r
o
m
wea
r
ab
le
d
ev
ices
u
s
in
g
clo
u
d
co
m
p
u
tin
g
an
d
m
ac
h
i
n
e
lear
n
in
g
alg
o
r
ith
m
s
.
J
o
b
s
atis
f
ac
tio
n
,
b
u
r
n
o
u
t
r
e
d
u
ctio
n
,
a
n
d
q
u
ality
o
f
p
atien
t
tr
ea
tm
en
t
ar
e
all
h
ig
h
lig
h
te
d
.
Fu
r
th
er
m
o
r
e,
it
h
ig
h
lig
h
ts
th
e
n
ee
d
to
im
p
r
o
v
e
f
u
r
th
er
an
d
en
s
u
r
e
wid
er
ad
o
p
tio
n
to
g
et
th
e
b
est r
esu
lts
.
I
n
s
u
m
,
th
e
co
n
v
er
s
atio
n
d
e
m
o
n
s
tr
ates h
o
w
tech
n
o
lo
g
y
m
ay
p
o
s
itiv
ely
im
p
ac
t
h
ea
lth
ca
r
e
wo
r
k
er
s
'
m
en
tal
h
ea
lth
,
im
p
r
o
v
in
g
p
atien
t o
u
tc
o
m
es a
n
d
cr
ea
tin
g
a
m
o
r
e
r
esil
ien
t staf
f
.
3
.
2
.
1
.
H
ea
lt
hca
re
wo
r
k
er
da
t
a
s
et
o
v
er
v
iew
T
ab
le
1
d
is
p
lay
s
a
d
ataset
u
s
e
d
to
f
o
r
ec
ast
h
ea
lth
ca
r
e
wo
r
k
e
r
s
'
welf
ar
e.
T
h
e
u
s
er
o
r
g
an
ize
s
th
e
d
ata,
with
m
an
y
p
ar
am
eter
s
r
ec
o
r
d
ed
in
ea
ch
r
o
w.
T
h
ese
f
ea
tu
r
es
in
clu
d
e
HR
V,
s
tep
s
tak
en
,
s
leep
len
g
th
,
s
tr
ess
Star
t
Data
c
o
llec
tio
n
&
p
r
ep
r
o
ce
s
s
in
g
Mo
d
el
tr
ain
in
g
&
ev
o
lu
tio
n
Dep
lo
y
m
en
t
Pre
d
ictio
n
En
d
End
Gr
ad
ien
t
b
o
o
stin
g
m
o
d
e
l
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
1
2
1
8
-
1
2
2
8
1224
lev
el,
s
k
in
tem
p
er
atu
r
e,
ac
tiv
it
y
lev
el,
r
esp
ir
ato
r
y
r
ate,
q
u
ality
o
f
s
leep
,
an
d
em
o
tio
n
al
well
-
b
ein
g
s
co
r
e.
Yo
u
ca
n
s
ee
wh
eth
er
th
e
u
s
er
is
u
n
d
er
a
lo
t
o
f
s
tr
ess
(
1
)
o
r
n
o
t
(
0
)
in
th
e
"
tar
g
et
v
a
r
iab
le
"
c
o
lu
m
n
.
Usi
n
g
th
is
d
ataset,
m
ac
h
in
e
lear
n
in
g
m
o
d
els
m
ay
b
e
tr
ain
ed
an
d
test
ed
to
f
o
r
ec
ast
th
e
s
tr
ess
lev
el
s
o
f
h
ea
lth
ca
r
e
wo
r
k
er
s
ac
co
r
d
in
g
to
t
h
eir
b
e
h
av
io
r
a
l
an
d
p
h
y
s
io
lo
g
ical
tr
aits
.
T
h
e
g
o
al
v
ar
iab
le
allo
ws
s
u
p
er
v
is
ed
lear
n
in
g
to
f
o
r
ec
ast
s
tr
ess
lev
el
s
,
wh
ile
t
h
e
ch
ar
ac
ter
is
tics
p
r
o
v
id
e
u
s
e
f
u
l
in
s
ig
h
ts
in
to
p
o
s
s
ib
le
ca
u
s
es
im
p
ac
tin
g
well
-
b
ein
g
.
Hea
lth
ca
r
e
w
o
r
k
er
ass
is
tan
ce
p
r
ac
tices m
ay
b
e
b
etter
u
n
d
er
s
to
o
d
an
d
im
p
r
o
v
ed
u
s
in
g
th
is
d
ataset.
T
ab
le
1
.
Hea
lth
wo
r
k
er
well
-
b
ein
g
d
ata
U
ser
H
e
a
r
t
r
a
t
e
v
a
r
i
a
b
i
l
i
t
y
S
t
e
p
s
t
a
k
e
n
S
l
e
e
p
d
u
r
a
t
i
o
n
S
t
r
e
ss
l
e
v
e
l
S
k
i
n
t
e
m
p
e
r
a
t
u
r
e
A
c
t
i
v
i
t
y
l
e
v
e
l
G
a
l
v
a
n
i
c
sk
i
n
r
e
sp
o
n
s
e
R
e
s
p
i
r
a
t
o
r
y
r
a
t
e
Q
u
a
l
i
t
y
o
f
sl
e
e
p
Emo
t
i
o
n
a
l
w
e
l
l
-
b
e
i
n
g
s
c
o
r
e
Ta
r
g
e
t
v
a
r
i
a
b
l
e
1
0
.
5
3
0
0
0
7
.
5
3
3
2
.
5
0
.
8
4
.
2
16
7
8
0
2
0
.
8
5
0
0
0
6
.
2
2
3
3
.
0
1
.
2
3
.
8
18
8
7
1
3
0
.
6
4
0
0
0
8
.
0
4
32
1
4
15
6
6
1
4
0
.
7
3
5
0
0
7
.
8
3
3
2
.
8
0
.
9
4
.
5
17
7
.
5
9
0
5
0
.
9
4
5
0
0
6
.
5
2
3
3
.
2
1
.
1
3
.
5
19
8
.
5
8
1
3
.
2
.
2
.
G
ra
dient
bo
o
s
t
ing
s
t
re
s
s
pre
dict
io
n
T
h
e
s
tr
ess
lev
el
s
p
r
ed
icted
b
y
a
g
r
ad
ien
t
-
b
o
o
s
tin
g
m
o
d
el
f
o
r
d
if
f
er
e
n
t
h
ea
lth
ca
r
e
p
r
o
f
ess
io
n
als
ar
e
s
h
o
wn
in
T
ab
le
2
.
E
ac
h
wo
r
k
er
'
s
ac
tu
al
o
r
r
ep
o
r
ted
s
tr
ess
lev
els
ar
e
k
ep
t
in
th
e
"Ac
tu
al
s
tr
ess
lev
el
"
co
lu
m
n
,
wh
ile
th
e
m
o
d
el'
s
p
r
ed
icted
s
tr
ess
lev
els
ar
e
s
h
o
wn
in
th
e
"
Pre
d
icted
s
tr
ess
lev
el
"
co
lu
m
n
.
User
s
ca
n
s
ee
h
o
w
well
th
e
m
o
d
el
p
r
ed
icts
h
ea
lth
ca
r
e
wo
r
k
er
s
'
s
tr
es
s
lev
els
b
y
co
m
p
ar
in
g
th
ese
two
s
e
ts
o
f
d
ata.
I
f
th
e
an
ticip
ated
an
d
ac
tu
al
s
tr
ess
le
v
els
do
n
ot
m
atch
u
p
,
it
m
ig
h
t
in
d
icate
th
at
th
e
m
o
d
el
n
ee
d
s
s
o
m
e
wo
r
k
.
B
etter
s
tr
ess
lev
el
p
r
o
jectio
n
s
an
d
s
u
p
p
o
r
t
m
ea
s
u
r
es
f
o
r
h
ea
lth
ca
r
e
wo
r
k
er
s
ar
e
p
o
s
s
ib
le
th
an
k
s
to
th
is
ev
alu
atio
n
,
wh
ich
h
elp
s
f
in
e
-
t
u
n
e
th
e
m
o
d
el
to
r
ef
lect
th
e
in
tr
icac
ies o
f
wo
r
k
er
well
-
b
ein
g
b
etter
.
T
ab
le
2
.
Hea
lth
ca
r
e
w
o
r
k
er
s
tr
ess
p
r
ed
ictio
n
U
ser
A
c
t
u
a
l
st
r
e
ss
l
e
v
e
l
P
r
e
d
i
c
t
e
d
st
r
e
ss
l
e
v
e
l
1
0
0
2
1
1
3
1
0
4
0
0
5
1
1
Fo
r
v
ar
io
u
s
g
r
ad
ien
t
-
b
o
o
s
tin
g
m
o
d
el
class
if
icatio
n
th
r
esh
o
ld
s
,
th
e
tr
ad
e
-
o
f
f
b
etwe
en
th
e
tr
u
e
p
o
s
itiv
e
r
ate
(
s
en
s
itiv
ity
)
an
d
th
e
f
alse
p
o
s
itiv
e
r
ate
(
1
-
s
p
ec
if
icity
)
g
r
ap
h
ically
r
ep
r
esen
ts
th
e
R
OC
cu
r
v
e
in
Fig
u
r
e
3
.
W
h
er
e
th
e
m
o
d
el
ac
h
iev
es
h
i
g
h
tr
u
e
p
o
s
itiv
e
r
ates
wh
ile
k
ee
p
in
g
l
o
w
f
alse
p
o
s
itiv
e
r
a
tes
ac
r
o
s
s
m
u
ltip
le
th
r
esh
o
ld
s
,
a
c
u
r
v
e
clo
s
er
to
th
e
to
p
-
lef
t
co
r
n
er
i
n
d
icate
s
s
tr
o
n
g
er
d
is
cr
im
in
atin
g
p
o
w
er
.
Hig
h
er
v
alu
es
in
d
icate
g
r
ea
ter
d
is
cr
im
in
atio
n
b
etwe
en
p
o
s
itiv
e
a
n
d
n
eg
at
iv
e
ca
s
es.
T
h
e
AUC
-
R
O
C
q
u
an
tifie
s
th
e
m
o
d
el'
s
o
v
er
all
p
er
f
o
r
m
an
ce
.
E
s
s
en
tial
ly
,
th
e
R
OC
cu
r
v
e
aid
s
in
ev
a
lu
atin
g
th
e
m
o
d
el'
s
clas
s
s
ep
a
r
atio
n
p
er
f
o
r
m
an
ce
an
d
ch
o
o
s
in
g
th
e
b
est
class
if
icatio
n
th
r
esh
o
ld
.
Fig
u
r
e
4
s
h
o
ws
th
e
tr
ad
e
-
o
f
f
b
etwe
en
r
ec
a
ll
(
s
en
s
itiv
ity
)
an
d
p
r
ec
is
io
n
(
p
o
s
itiv
e
p
r
ed
ictiv
e
v
alu
e)
f
o
r
v
a
r
io
u
s
g
r
a
d
ien
t
-
b
o
o
s
tin
g
m
o
d
el
ca
teg
o
r
izatio
n
t
h
r
esh
o
ld
s
.
Fig
u
r
e
3
.
Gr
a
d
ien
t b
o
o
s
tin
g
m
o
d
el
R
OC
an
aly
s
is
Fig
u
r
e
4
.
Pre
cisi
o
n
-
r
ec
all
cu
r
v
e
f
o
r
g
r
ad
ien
t
b
o
o
s
tin
g
m
o
d
el
0
0.
2
0.
4
0.
6
0.
8
1
1.
2
0
0.
1
0
.
2
0.
3
0.
4
0.
5
0.
6
0.
7
0.
8
0.
9
Th
r
e
sh
o
ld
Fa
l
se
Po
si
t
i
v
e
R
a
t
e
(
FP
R
)
T
r
u
e
Po
si
t
i
v
e
R
a
t
e
(
T
PR
)
R
OC
C
u
r
v
e
0
0.
2
0.
4
0.
6
0.
8
1
1.
2
1.
4
1.
6
0
0.
1
0.
2
0.
3
0.
4
0.
5
0.
6
0.
7
0.
8
0.
9
1
R
e
c
a
l
l
Pr
e
c
i
si
o
n
Th
r
e
sh
o
ld
P
re
c
isio
n
Re
c
a
ll
Cu
rv
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
r
ed
ictive
mo
d
elin
g
fo
r
h
ea
lth
ca
r
e
w
o
r
ke
r
w
e
ll
-
b
ein
g
w
ith
clo
u
d
…
(
Mu
t
h
u
ka
th
a
n
R
a
jen
d
r
a
n
S
u
d
h
a
)
1225
W
o
r
k
in
g
with
u
n
b
alan
ce
d
d
a
tasets
i
s
v
er
y
h
elp
f
u
l.
W
h
en
th
e
m
o
d
el
s
u
cc
ess
f
u
lly
d
etec
t
s
p
o
s
itiv
e
o
cc
u
r
r
e
n
ce
s
wh
ile
lim
itin
g
f
al
s
e
p
o
s
itiv
es,
its
ac
cu
r
ac
y
an
d
r
ec
all
ar
e
g
r
ea
ter
,
as
s
h
o
wn
b
y
a
c
u
r
v
e
clo
s
er
t
o
th
e
to
p
-
r
i
g
h
t
co
r
n
er
.
T
h
e
ar
e
a
u
n
d
er
th
e
ac
cu
r
ac
y
-
r
ec
all
c
u
r
v
e
m
ea
s
u
r
es
th
e
m
o
d
el'
s
o
v
er
all
p
er
f
o
r
m
an
ce
,
wh
er
e
lar
g
er
v
alu
es
c
o
r
r
esp
o
n
d
to
im
p
r
o
v
ed
r
ec
all
an
d
ac
cu
r
ac
y
.
T
h
e
p
r
ec
is
io
n
-
r
ec
all
cu
r
v
e
ess
en
tially
aid
s
in
ev
alu
atin
g
t
h
e
m
o
d
el'
s
ca
p
ac
ity
to
ca
teg
o
r
ize
p
o
s
itiv
e
ca
s
es wh
ile
ac
co
u
n
tin
g
f
o
r
f
alse p
o
s
itiv
es a
cc
u
r
ately
.
Fig
u
r
e
5
g
r
ap
h
s
h
o
ws
th
e
g
r
a
d
ien
t
b
o
o
s
tin
g
m
o
d
el'
s
p
er
f
o
r
m
an
ce
m
etr
ics
ac
r
o
s
s
s
ev
er
al
iter
atio
n
s
.
T
h
e
g
r
ap
h
'
s
p
o
in
ts
co
r
r
esp
o
n
d
to
th
e
m
o
d
el'
s
AU
C
-
R
O
C
,
F1
-
s
co
r
e,
r
ec
all,
ac
cu
r
ac
y
,
an
d
p
r
ec
is
io
n
at
a
p
ar
ticu
lar
iter
atio
n
.
I
t
ca
n
m
o
n
ito
r
th
e
ev
o
lu
tio
n
o
f
th
e
m
o
d
el's
p
er
f
o
r
m
an
ce
d
u
r
i
n
g
tr
ain
i
n
g
b
y
k
ee
p
in
g
tr
ac
k
o
f
th
ese
m
ea
s
u
r
es
th
r
o
u
g
h
o
u
t
s
ev
er
al
iter
atio
n
s
.
Per
f
o
r
m
an
ce
in
d
icato
r
s
s
h
o
u
ld
id
ea
lly
co
n
v
er
g
e
to
s
tab
le
v
alu
es
o
r
in
cr
ea
s
e
g
r
a
d
u
ally
o
v
er
tim
e
to
en
s
u
r
e
th
at
t
h
e
m
o
d
el
is
lear
n
in
g
ef
f
icien
tly
.
C
h
an
g
es
to
th
e
m
o
d
el
o
r
tr
ain
i
n
g
p
r
o
ce
d
u
r
e
m
ay
b
e
n
ec
ess
ar
y
to
im
p
r
o
v
e
p
er
f
o
r
m
an
ce
if
d
ev
iatio
n
s
o
r
v
ar
iati
o
n
s
in
t
h
e
m
etr
ics
p
o
in
t to
p
r
o
b
lem
s
lik
e
o
v
er
f
itti
n
g
o
r
u
n
d
er
f
itti
n
g
.
Fig
u
r
e
5
.
Gr
a
d
ien
t
b
o
o
s
tin
g
it
er
atio
n
p
er
f
o
r
m
a
n
ce
3
.
2
.
3
.
K
ey
b
enef
it
s
a
nd
i
m
pli
ca
t
io
ns
Th
e
k
ey
b
en
ef
its
an
d
im
p
licatio
n
s
o
f
th
is
r
esear
ch
i
n
clu
d
e
:
a.
Pro
ac
tiv
e
s
tr
ess
m
an
ag
em
en
t
:
T
h
e
h
ea
lth
ca
r
e
in
d
u
s
tr
y
m
ay
b
etter
p
r
o
tect
its
em
p
lo
y
ee
s
f
r
o
m
im
p
e
n
d
in
g
s
tr
ess
b
y
u
s
in
g
p
r
ed
ictiv
e
m
o
d
elin
g
to
f
o
r
esee
p
o
s
s
ib
le
p
r
o
b
l
em
s
an
d
tak
e
p
r
ev
en
tativ
e
m
e
asu
r
es.
b.
I
m
p
r
o
v
ed
p
atien
t
ca
r
e:
T
h
e
h
e
alth
an
d
r
esil
ien
ce
o
f
th
e
wo
r
k
f
o
r
ce
d
ir
ec
tly
im
p
ac
t
th
e
q
u
ali
ty
o
f
tr
ea
tm
en
t
th
at
p
atien
ts
g
et.
Hea
lth
ca
r
e
p
er
s
o
n
n
el
r
ep
o
r
t
m
o
r
e
j
o
b
s
atis
f
ac
tio
n
an
d
b
etter
p
atien
t
ca
r
e
wh
en
th
ey
ex
p
er
ien
ce
less
s
tr
ess
an
d
b
u
r
n
o
u
t.
c.
R
eso
u
r
ce
o
p
tim
izatio
n
:
Me
d
ical
in
s
titu
tio
n
s
m
ay
m
ak
e
b
etter
u
s
e
o
f
th
eir
co
m
p
u
ter
r
eso
u
r
ce
s
f
o
r
tr
ain
in
g
an
d
d
ep
lo
y
in
g
m
o
d
els
with
th
e
h
elp
o
f
clo
u
d
co
m
p
u
tin
g
in
f
r
astru
ctu
r
e,
wh
ic
h
is
b
o
th
af
f
o
r
d
a
b
le
an
d
s
ca
lab
le.
d.
Data
-
d
r
iv
en
d
ec
is
io
n
-
m
ak
in
g
:
Hea
lth
ca
r
e
o
r
g
an
izatio
n
s
m
a
y
u
s
e
d
ata
a
n
aly
tics
an
d
m
ac
h
in
e
lear
n
in
g
to
m
ak
e
s
m
ar
t c
h
o
ices a
b
o
u
t stre
s
s
m
an
ag
em
en
t in
ter
v
e
n
tio
n
p
r
io
r
itizatio
n
an
d
wo
r
k
f
o
r
ce
o
p
tim
izatio
n
.
4.
CO
NCLU
SI
O
N
Fin
ally
,
th
e
estab
lis
h
ed
s
y
s
te
m
h
as
g
r
ea
tly
ad
v
an
ce
d
h
ea
lt
h
ca
r
e
wo
r
k
er
s
'
well
-
b
ein
g
v
ia
p
r
o
ac
tiv
e
s
tr
ess
m
an
ag
em
en
t.
T
ec
h
n
o
l
o
g
y
p
r
o
v
id
es
h
ea
lth
ca
r
e
p
r
o
v
id
er
s
with
s
ca
lab
le,
d
ata
-
d
r
iv
en
tr
ea
tm
e
n
ts
cu
s
to
m
ized
to
th
ei
r
s
p
ec
if
ic
r
eq
u
ir
em
e
n
ts
u
s
in
g
clo
u
d
co
m
p
u
tin
g
a
n
d
m
ac
h
in
e
lea
r
n
i
n
g
.
I
t
h
elp
s
r
e
d
u
ce
b
u
r
n
o
u
t
an
d
p
r
o
m
o
te
m
en
tal
h
ea
lth
b
y
co
n
tin
u
o
u
s
ly
m
o
n
it
o
r
in
g
b
eh
av
i
o
r
al
an
d
p
h
y
s
io
lo
g
ical
s
ig
n
s
u
s
in
g
wea
r
ab
le
d
ev
ices.
T
h
is
allo
ws
f
o
r
ea
r
l
y
d
iag
n
o
s
is
o
f
s
tr
ess
p
atter
n
s
an
d
p
r
o
m
p
t
in
ter
v
en
tio
n
.
W
ith
alg
o
r
ith
m
s
s
u
ch
as
g
r
ad
ie
n
t
b
o
o
s
tin
g
,
t
h
e
s
y
s
tem
's
p
r
ed
ictiv
e
m
o
d
elin
g
co
m
p
o
n
e
n
t
ca
n
ac
cu
r
ately
esti
m
ate
th
e
s
tr
es
s
lev
els
o
f
h
ea
lth
ca
r
e
w
o
r
k
er
s
.
T
h
is
allo
ws
b
u
s
in
ess
es
to
tr
ea
t
an
d
p
r
ev
e
n
t
s
tr
ess
p
r
o
ac
tiv
e
ly
.
I
ts
clo
u
d
-
b
ased
ar
ch
itectu
r
e
also
g
u
a
r
an
tees a
cc
ess
ib
ilit
y
,
d
ep
en
d
ab
ilit
y
,
an
d
s
ca
lab
ilit
y
,
wh
ich
m
ak
es it e
asy
to
in
teg
r
ate
with
o
th
er
h
ea
lth
ca
r
e
I
T
s
y
s
tem
s
a
n
d
e
n
co
u
r
a
g
es
b
r
o
ad
ad
o
p
tio
n
.
I
t
m
u
s
t
b
e
f
in
e
-
t
u
n
ed
an
d
o
p
t
im
ized
ev
en
f
u
r
th
er
to
g
et
m
o
s
t
o
f
th
e
s
y
s
tem
g
o
in
g
ah
ea
d
.
T
o
cu
ltiv
ate
a
cu
ltu
r
e
o
f
welln
ess
an
d
r
esil
ien
ce
am
o
n
g
h
ea
lth
ca
r
e
wo
r
k
er
s
,
it
is
im
p
o
r
tan
t
to
r
aise
awa
r
en
ess
an
d
ac
ce
p
tan
ce
a
m
o
n
g
h
ea
lth
ca
r
e
o
r
g
an
izatio
n
s
an
d
p
r
o
f
ess
io
n
als.
Mo
r
e
jo
b
s
atis
f
ac
tio
n
,
less
b
u
r
n
o
u
t,
an
d
b
etter
p
atien
t
ca
r
e
a
r
e
all
p
o
s
s
ib
le
o
u
tco
m
es
o
f
th
e
s
y
s
tem
'
s
p
o
ten
tial
to
tr
an
s
f
o
r
m
h
ea
lth
ca
r
e
wo
r
k
er
well
-
b
ein
g
p
r
o
g
r
am
s
.
I
t
m
ig
h
t
im
p
r
o
v
e
th
e
h
ea
lth
ca
r
e
s
y
s
tem
an
d
lead
to
b
etter
r
esu
lts
f
o
r
d
o
cto
r
s
an
d
p
atien
ts
if
p
eo
p
le
k
ee
p
in
v
e
n
tin
g
an
d
wo
r
k
in
g
to
g
eth
e
r
.
0
0
.
2
0
.
4
0
.
6
0
.
8
1
1
2
3
4
5
I
t
e
r
a
t
i
o
n
A
c
c
u
r
a
c
y
P
r
e
c
i
si
o
n
R
e
c
a
l
l
F
1
S
c
o
r
e
A
U
C
-
R
O
C
P
e
r
f
o
r
man
c
e
M
e
t
r
i
c
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
1
2
1
8
-
1
2
2
8
1226
RE
F
E
R
E
NC
E
S
[
1
]
R
.
G
.
B
a
n
g
a
n
i
,
V
.
M
e
n
o
n
,
a
n
d
E.
Jo
v
a
n
o
v
,
“
P
e
r
so
n
a
l
i
z
e
d
s
t
r
e
ss
m
o
n
i
t
o
r
i
n
g
A
I
sy
st
e
m
f
o
r
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s,”
i
n
2
0
2
1
I
EEE
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
B
i
o
i
n
f
o
rm
a
t
i
c
s
a
n
d
Bi
o
m
e
d
i
c
i
n
e
(
BI
B
M)
,
D
e
c
.
2
0
2
1
,
p
p
.
2
9
9
2
–
2
9
9
7
,
d
o
i
:
1
0
.
1
1
0
9
/
B
I
B
M
5
2
6
1
5
.
2
0
2
1
.
9
6
6
9
3
2
1
.
[
2
]
M
.
A
.
F
a
u
z
i
,
P
.
Y
e
n
g
,
a
n
d
B
.
Y
a
n
g
,
“
C
o
r
r
e
l
a
t
i
n
g
h
e
a
l
t
h
c
a
r
e
s
t
a
f
f
’
s
st
r
e
ss
l
e
v
e
l
a
n
d
c
y
b
e
r
sec
u
r
i
t
y
p
r
a
c
t
i
c
e
s
i
n
N
o
r
w
a
y
,
”
i
n
2
0
2
3
I
n
t
e
l
l
i
g
e
n
t
Me
t
h
o
d
s,
S
y
st
e
m
s
,
a
n
d
Ap
p
l
i
c
a
t
i
o
n
s
(
I
MS
A)
,
J
u
l
.
2
0
2
3
,
p
p
.
2
3
5
–
2
4
0
,
d
o
i
:
1
0
.
1
1
0
9
/
I
M
S
A
5
8
5
4
2
.
2
0
2
3
.
1
0
2
1
7
7
8
3
.
[
3
]
P
.
G
u
p
t
a
,
S
.
M
a
j
i
,
a
n
d
R
.
M
e
h
r
a
,
“
P
r
e
d
i
c
t
i
v
e
m
o
d
e
l
i
n
g
o
f
h
e
a
l
t
h
c
a
r
e
p
r
o
f
e
s
s
i
o
n
a
l
’
s
s
t
r
e
s
s
b
a
s
e
d
o
n
X
G
B
o
o
s
t
m
o
d
e
l
,
”
i
n
2
0
2
1
I
E
E
E
1
8
t
h
I
n
d
i
a
C
o
u
n
c
i
l
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
(
I
N
D
I
C
O
N
)
,
D
e
c
.
2
0
2
1
,
p
p
.
1
–
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
N
D
I
C
O
N
5
2
5
7
6
.
2
0
2
1
.
9
6
9
1
7
2
5
.
[
4
]
V
.
R
a
v
u
r
i
e
t
a
l
.
,
“
G
r
o
u
p
-
s
p
e
c
i
f
i
c
m
o
d
e
l
s
o
f
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s’
w
e
l
l
-
b
e
i
n
g
u
si
n
g
i
t
e
r
a
t
i
v
e
p
a
r
t
i
c
i
p
a
n
t
c
l
u
s
t
e
r
i
n
g
,
”
i
n
2
0
2
0
S
e
c
o
n
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
T
r
a
n
sd
i
s
c
i
p
l
i
n
a
ry
AI
(
T
ra
n
sAI
)
,
S
e
p
.
2
0
2
0
,
p
p
.
1
1
5
–
1
1
8
,
d
o
i
:
1
0
.
1
1
0
9
/
Tr
a
n
sA
I
4
9
8
3
7
.
2
0
2
0
.
0
0
0
2
6
.
[
5
]
M
.
J
a
v
i
e
r
r
e
e
t
a
l
.
,
“
Q
u
a
n
t
i
f
i
c
a
t
i
o
n
o
f
st
r
e
ss
a
n
d
d
e
p
r
e
ss
i
o
n
l
e
v
e
l
p
o
se
d
b
y
C
O
V
I
D
-
1
9
i
n
f
i
r
st
-
l
i
n
e
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s,”
i
n
2
0
2
2
1
2
t
h
C
o
n
f
e
r
e
n
c
e
o
f
t
h
e
E
u
ro
p
e
a
n
S
t
u
d
y
G
ro
u
p
o
n
C
a
r
d
i
o
v
a
s
c
u
l
a
r
O
sci
l
l
a
t
i
o
n
s
(
ES
G
C
O
)
,
O
c
t
.
2
0
2
2
,
p
p
.
1
–
2
,
d
o
i
:
1
0
.
1
1
0
9
/
ESG
C
O
5
5
4
2
3
.
2
0
2
2
.
9
9
3
1
3
5
9
.
[
6
]
K
a
v
y
a
s
h
r
e
e
N
a
n
d
U
s
h
a
J,
“
M
e
d
i
B
o
t
:
h
e
a
l
t
h
c
a
r
e
a
ssi
s
t
a
n
t
o
n
me
n
t
a
l
h
e
a
l
t
h
a
n
d
w
e
l
l
b
e
i
n
g
,
”
i
n
2
0
2
3
7
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
a
t
i
o
n
S
y
st
e
m
a
n
d
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
y
f
o
r
S
u
s
t
a
i
n
a
b
l
e
S
o
l
u
t
i
o
n
s
(
C
S
I
T
S
S
)
,
N
o
v
.
2
0
2
3
,
p
p
.
1
–
5
,
d
o
i
:
1
0
.
1
1
0
9
/
C
S
I
TSS
6
0
5
1
5
.
2
0
2
3
.
1
0
3
3
4
0
8
3
.
[
7
]
B
.
J
.
G
a
n
e
s
h
,
P
.
V
i
j
a
y
a
n
,
V
.
V
a
i
d
e
h
i
,
S
.
M
u
r
u
g
a
n
,
R
.
M
e
e
n
a
k
s
h
i
,
a
n
d
M
.
R
a
j
m
o
h
a
n
,
“
S
V
M
-
b
a
s
e
d
p
r
e
d
i
c
t
i
v
e
m
o
d
e
l
i
n
g
o
f
d
r
o
w
s
i
n
e
ss
i
n
h
o
sp
i
t
a
l
st
a
f
f
f
o
r
o
c
c
u
p
a
t
i
o
n
a
l
saf
e
t
y
so
l
u
t
i
o
n
v
i
a
I
o
T
i
n
f
r
a
st
r
u
c
t
u
r
e
,
”
i
n
2
0
2
4
2
n
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
e
r
,
C
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
C
o
n
t
r
o
l
(
I
C
4
)
,
F
e
b
.
2
0
2
4
,
p
p
.
1
–
5
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
4
5
7
4
3
4
.
2
0
2
4
.
1
0
4
8
6
4
2
9
.
[
8
]
L.
N
i
n
g
e
t
a
l
.
,
“
Th
e
me
d
i
a
t
i
n
g
r
o
l
e
o
f
j
o
b
sa
t
i
sf
a
c
t
i
o
n
a
n
d
p
r
e
s
e
n
t
e
e
i
sm
o
n
t
h
e
r
e
l
a
t
i
o
n
s
h
i
p
b
e
t
w
e
e
n
j
o
b
s
t
r
e
ss
a
n
d
t
u
r
n
o
v
e
r
i
n
t
e
n
t
i
o
n
a
m
o
n
g
p
r
i
m
a
r
y
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s,”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
f
o
r
Eq
u
i
t
y
i
n
H
e
a
l
t
h
,
v
o
l
.
2
2
,
n
o
.
1
,
p
p
.
1
–
9
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
8
6
/
s
1
2
9
3
9
-
0
2
3
-
0
1
9
7
1
-
x.
[
9
]
J.
L.
C
a
h
o
o
n
a
n
d
L
.
A
.
G
a
r
c
i
a
,
“
C
o
n
t
i
n
u
o
u
s
s
t
r
e
ss
m
o
n
i
t
o
r
i
n
g
f
o
r
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s
:
e
v
a
l
u
a
t
i
n
g
g
e
n
e
r
a
l
i
z
a
b
i
l
i
t
y
a
c
r
o
ss
r
e
a
l
-
w
o
r
l
d
d
a
t
a
se
t
s,”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
1
4
t
h
A
C
M
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
Bi
o
i
n
f
o
rm
a
t
i
c
s,
C
o
m
p
u
t
a
t
i
o
n
a
l
Bi
o
l
o
g
y
,
a
n
d
H
e
a
l
t
h
I
n
f
o
rm
a
t
i
c
s
,
S
e
p
.
2
0
2
3
,
p
p
.
1
–
5
,
d
o
i
:
1
0
.
1
1
4
5
/
3
5
8
4
3
7
1
.
3
6
1
2
9
7
4
.
[
1
0
]
L.
E
.
S
ø
v
o
l
d
e
t
a
l
.
,
“
P
r
i
o
r
i
t
i
z
i
n
g
t
h
e
men
t
a
l
h
e
a
l
t
h
a
n
d
w
e
l
l
-
b
e
i
n
g
o
f
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s:
a
n
u
r
g
e
n
t
g
l
o
b
a
l
p
u
b
l
i
c
h
e
a
l
t
h
p
r
i
o
r
i
t
y
,
”
Fro
n
t
i
e
rs
i
n
P
u
b
l
i
c
H
e
a
l
t
h
,
v
o
l
.
9
,
M
a
y
2
0
2
1
,
d
o
i
:
1
0
.
3
3
8
9
/
f
p
u
b
h
.
2
0
2
1
.
6
7
9
3
9
7
.
[
1
1
]
N
.
Z
h
o
l
d
a
s,
O
.
P
o
st
o
l
a
c
h
e
,
M
.
M
a
n
s
u
r
o
v
a
,
B
.
B
e
l
g
i
b
a
e
v
,
M
.
K
u
n
e
l
b
a
y
e
v
,
a
n
d
T
.
S
a
r
s
e
mb
a
y
e
v
a
,
“
D
e
v
e
l
o
p
me
n
t
o
f
a
w
e
a
r
a
b
l
e
mo
n
i
t
o
r
t
o
i
d
e
n
t
i
f
y
st
r
e
s
s
l
e
v
e
l
s
u
s
i
n
g
i
n
t
e
r
n
e
t
o
f
t
h
i
n
g
s,”
I
n
d
o
n
e
si
a
n
J
o
u
rn
a
l
o
f
El
e
c
t
ri
c
a
l
E
n
g
i
n
e
e
ri
n
g
a
n
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
3
3
,
n
o
.
3
,
p
p
.
1
4
8
6
–
1
4
9
9
,
M
a
r
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
e
e
c
s.
v
3
3
.
i
3
.
p
p
1
4
8
6
-
1
4
9
9
.
[
1
2
]
J.
La
i
e
t
a
l
.
,
“
F
a
c
t
o
r
s
a
ss
o
c
i
a
t
e
d
w
i
t
h
men
t
a
l
h
e
a
l
t
h
o
u
t
c
o
m
e
s
a
mo
n
g
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s
e
x
p
o
se
d
t
o
c
o
r
o
n
a
v
i
r
u
s
d
i
s
e
a
s
e
2
0
1
9
,
”
J
AM
A
N
e
t
w
o
r
k
O
p
e
n
,
v
o
l
.
3
,
n
o
.
3
,
M
a
r
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
0
1
/
j
a
ma
n
e
t
w
o
r
k
o
p
e
n
.
2
0
2
0
.
3
9
7
6
.
[
1
3
]
R
.
P
a
r
t
h
a
sara
t
h
y
,
J
.
TS,
T.
K
,
a
n
d
P
.
M
u
r
t
h
y
,
“
M
e
n
t
a
l
h
e
a
l
t
h
i
ssu
e
s
a
m
o
n
g
h
e
a
l
t
h
c
a
r
e
w
o
r
k
e
r
s
d
u
r
i
n
g
t
h
e
C
O
V
I
D
-
1
9
p
a
n
d
e
mi
c
–
A
st
u
d
y
f
r
o
m
I
n
d
i
a
,
”
As
i
a
n
J
o
u
r
n
a
l
o
f
Psy
c
h
i
a
t
ry
,
v
o
l
.
5
8
,
A
p
r
.
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
a
j
p
.
2
0
2
1
.
1
0
2
6
2
6
.
[
1
4
]
S
.
T
i
v
a
t
a
n
s
a
k
u
l
a
n
d
M
.
O
h
k
u
r
a
,
“
I
mp
r
o
v
e
m
e
n
t
o
f
e
m
o
t
i
o
n
a
l
h
e
a
l
t
h
c
a
r
e
s
y
st
e
m
w
i
t
h
st
r
e
ss
d
e
t
e
c
t
i
o
n
f
r
o
m
EC
G
si
g
n
a
l
,
”
i
n
2
0
1
5
3
7
t
h
A
n
n
u
a
l
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
f
t
h
e
I
EEE
En
g
i
n
e
e
ri
n
g
i
n
Me
d
i
c
i
n
e
a
n
d
B
i
o
l
o
g
y
S
o
c
i
e
t
y
(
EM
BC
)
,
A
u
g
.
2
0
1
5
,
p
p
.
6
7
9
2
–
6
7
9
5
,
d
o
i
:
1
0
.
1
1
0
9
/
E
M
B
C
.
2
0
1
5
.
7
3
1
9
9
5
3
.
[
1
5
]
H
.
P
a
r
k
a
n
d
S
.
H
a
h
m,
“
C
h
a
n
g
e
s
i
n
st
r
e
ss
mi
n
d
se
t
a
n
d
EEG
t
h
r
o
u
g
h
E
-
h
e
a
l
t
h
c
a
r
e
b
a
s
e
d
e
d
u
c
a
t
i
o
n
,
”
I
EE
E
Ac
c
e
ss
,
v
o
l
.
7
,
p
p
.
2
0
1
6
3
–
2
0
1
7
1
,
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
1
9
.
2
8
9
5
6
5
5
.
[
1
6
]
A
.
Ja
i
n
a
n
d
M
.
K
u
m
a
r
i
,
“
P
r
e
d
i
c
t
i
o
n
o
f
st
r
e
ss
u
s
i
n
g
ma
c
h
i
n
e
l
e
a
r
n
i
n
g
a
n
d
I
o
T,
”
i
n
2
0
2
2
1
1
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
S
y
st
e
m
Mo
d
e
l
i
n
g
&
Ad
v
a
n
c
e
m
e
n
t
i
n
R
e
se
a
rc
h
T
re
n
d
s (
S
MA
RT)
,
D
e
c
.
2
0
2
2
,
p
p
.
2
8
2
–
2
8
5
,
d
o
i
:
1
0
.
1
1
0
9
/
S
M
A
R
T5
5
8
2
9
.
2
0
2
2
.
1
0
0
4
6
9
0
7
.
[
1
7
]
A
sh
a
,
N
.
P
a
t
i
l
,
B
.
M
.
P
r
e
e
t
i
,
a
n
d
La
x
mi
,
“
R
e
a
l
-
t
i
me
s
t
r
e
ss
l
e
v
e
l
m
o
n
i
t
o
r
i
n
g
u
si
n
g
I
o
T,
”
i
n
2
0
2
3
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
t
e
g
r
a
t
e
d
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
S
y
st
e
m
s (I
C
I
I
C
S
)
,
N
o
v
.
2
0
2
3
,
p
p
.
1
–
4
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
I
I
C
S
5
9
9
9
3
.
2
0
2
3
.
1
0
4
2
1
6
9
4
.
[
1
8
]
G
.
R
i
b
e
i
r
o
a
n
d
O
.
P
o
s
t
o
l
a
c
h
e
,
“
N
e
w
a
p
p
r
o
a
c
h
f
o
r
s
t
r
e
ss
a
sses
sme
n
t
b
a
se
d
o
n
h
e
a
l
t
h
c
a
r
e
e
c
o
s
y
st
e
ms,”
i
n
2
0
2
3
I
EE
E
S
e
n
s
o
r
s
Ap
p
l
i
c
a
t
i
o
n
s
S
y
m
p
o
si
u
m
(
S
AS
)
,
J
u
l
.
2
0
2
3
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
S
A
S
5
8
8
2
1
.
2
0
2
3
.
1
0
2
5
4
0
4
5
.
[
1
9
]
A
.
H
e
n
d
r
y
a
n
i
,
D
.
G
u
n
a
w
a
n
,
M
.
R
i
z
k
i
n
i
a
,
R
.
N
u
r
H
i
d
a
y
a
t
i
,
a
n
d
F
.
Y
u
g
i
H
e
r
maw
a
n
,
“
R
e
a
l
-
t
i
m
e
s
t
r
e
ss
d
e
t
e
c
t
i
o
n
a
n
d
mo
n
i
t
o
r
i
n
g
sy
st
e
m
u
s
i
n
g
I
o
T
-
b
a
se
d
p
h
y
si
o
l
o
g
i
c
a
l
si
g
n
a
l
s
,
”
B
u
l
l
e
t
i
n
o
f
El
e
c
t
ri
c
a
l
En
g
i
n
e
e
ri
n
g
a
n
d
I
n
f
o
rm
a
t
i
c
s
,
v
o
l
.
1
2
,
n
o
.
5
,
p
p
.
2
8
0
7
–
2
8
1
5
,
O
c
t
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
5
9
1
/
e
e
i
.
v
1
2
i
5
.
5
1
3
2
.
[
2
0
]
M
.
P
r
i
y
a
D
,
H
.
H
a
r
a
n
S
,
B
.
R
o
h
i
t
h
,
H
a
r
i
p
r
a
s
a
t
h
M
,
a
n
d
J
.
K
u
m
a
r
P
,
“
D
e
t
e
c
t
i
o
n
o
f
st
r
e
ss
b
y
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
i
n
I
T
i
n
d
u
s
t
r
y
,
”
i
n
2
0
2
3
7
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
i
n
g
Me
t
h
o
d
o
l
o
g
i
e
s
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
(
I
C
C
M
C
)
,
F
e
b
.
2
0
2
3
,
p
p
.
5
3
–
5
6
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
C
M
C
5
6
5
0
7
.
2
0
2
3
.
1
0
0
8
3
8
8
4
.
[
2
1
]
U
.
S
.
R
e
d
d
y
,
A
.
V
.
T
h
o
t
a
,
a
n
d
A
.
D
h
a
r
u
n
,
“
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
t
e
c
h
n
i
q
u
e
s
f
o
r
st
r
e
s
s
p
r
e
d
i
c
t
i
o
n
i
n
w
o
r
k
i
n
g
e
m
p
l
o
y
e
e
s
,
”
i
n
2
0
1
8
I
EEE
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
a
t
i
o
n
a
l
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
C
o
m
p
u
t
i
n
g
R
e
se
a
rc
h
(
I
C
C
I
C
)
,
D
e
c
.
2
0
1
8
,
p
p
.
1
–
4
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
C
I
C
.
2
0
1
8
.
8
7
8
2
3
9
5
.
[
2
2
]
T.
R
.
P
.
H
.
S
.
R
.
,
D
.
D
.
M
.
D
.
M
.
,
N
.
M
.
D
.
S
.
,
P
.
A
.
D
.
Th
a
me
e
r
a
,
W
.
A
.
C
.
P
a
b
a
sara
,
a
n
d
H
.
A
.
C
a
l
d
e
r
a
,
“
W
o
r
k
l
o
a
d
man
a
g
e
me
n
t
s
y
st
e
m
f
o
r
I
T
p
r
o
f
e
ss
i
o
n
a
l
s
t
h
r
o
u
g
h
s
t
r
e
ss
i
d
e
n
t
i
f
i
c
a
t
i
o
n
,
”
I
n
t
e
rn
a
t
i
o
n
a
l
Re
se
a
r
c
h
J
o
u
rn
a
l
o
f
I
n
n
o
v
a
t
i
o
n
s
i
n
En
g
i
n
e
e
ri
n
g
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
7
,
n
o
.
1
0
,
p
p
.
3
2
6
–
3
3
2
,
2
0
2
3
.
[
2
3
]
A
.
H
i
n
z
e
,
J
.
B
o
w
e
n
,
a
n
d
J.
L.
K
ö
n
i
g
,
“
W
e
a
r
a
b
l
e
t
e
c
h
n
o
l
o
g
y
f
o
r
h
a
z
a
r
d
o
u
s
r
e
m
o
t
e
e
n
v
i
r
o
n
me
n
t
s
:
smar
t
s
h
i
r
t
a
n
d
r
u
g
g
e
d
I
o
T
n
e
t
w
o
r
k
f
o
r
f
o
r
e
s
t
r
y
w
o
r
k
e
r
h
e
a
l
t
h
,
”
S
m
a
rt
H
e
a
l
t
h
,
v
o
l
.
2
3
,
M
a
r
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
smh
l
.
2
0
2
1
.
1
0
0
2
2
5
.
[
2
4
]
S
u
h
a
s
K
S
a
n
d
P
h
a
n
e
e
n
d
r
a
H
D
,
“
S
t
r
e
ss
p
r
e
d
i
c
t
i
o
n
i
n
w
o
r
k
i
n
g
e
m
p
l
o
y
e
e
s
u
s
i
n
g
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
o
f
t
h
i
n
g
s
,
”
J
o
u
r
n
a
l
o
f
Ph
a
rm
a
c
e
u
t
i
c
a
l
N
e
g
a
t
i
v
e
R
e
su
l
t
s
,
v
o
l
.
1
3
,
n
o
.
1
,
Ja
n
.
2
0
2
2
,
d
o
i
:
1
0
.
4
7
7
5
0
/
p
n
r
.
2
0
2
2
.
1
3
.
S
0
1
.
2
3
7
.
[
2
5
]
R
.
S
h
a
r
ma,
S
.
R
a
n
i
,
a
n
d
D
.
G
u
p
t
a
,
“
S
t
r
e
ss
d
e
t
e
c
t
i
o
n
u
si
n
g
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
c
l
a
ssi
f
i
e
r
s
i
n
i
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s
e
n
v
i
r
o
n
me
n
t
,
”
J
o
u
rn
a
l
o
f
C
o
m
p
u
t
a
t
i
o
n
a
l
a
n
d
T
h
e
o
re
t
i
c
a
l
N
a
n
o
s
c
i
e
n
c
e
,
v
o
l
.
1
6
,
n
o
.
1
0
,
p
p
.
4
2
1
4
–
4
2
1
9
,
O
c
t
.
2
0
1
9
,
d
o
i
:
1
0
.
1
1
6
6
/
j
c
t
n
.
2
0
1
9
.
8
5
0
2
.
[
2
6
]
L.
M
a
l
v
i
y
a
e
t
a
l
.
,
“
M
e
n
t
a
l
st
r
e
ss
l
e
v
e
l
d
e
t
e
c
t
i
o
n
u
s
i
n
g
LST
M
f
o
r
W
ES
A
D
d
a
t
a
s
e
t
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
D
a
t
a
An
a
l
y
t
i
c
s
a
n
d
Ma
n
a
g
e
m
e
n
t
:
I
C
D
AM
2
0
2
2
,
2
0
2
3
,
p
p
.
2
4
3
–
2
5
0
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
9
8
1
-
19
-
7
6
1
5
-
5
_
2
2
.
[
2
7
]
A
.
M
u
s
t
a
f
a
,
M
.
A
l
a
h
me
d
,
A
.
A
l
h
a
m
mad
i
,
a
n
d
B
.
S
o
u
d
a
n
,
“
S
t
r
e
ss
d
e
t
e
c
t
o
r
sy
s
t
e
m
u
si
n
g
I
o
T
a
n
d
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
,
”
i
n
2
0
2
0
Ad
v
a
n
c
e
s
i
n
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
ri
n
g
T
e
c
h
n
o
l
o
g
y
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
s
(
A
S
ET)
,
F
e
b
.
2
0
2
0
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
A
S
ET
4
8
3
9
2
.
2
0
2
0
.
9
1
1
8
3
4
5
.
[
2
8
]
S
.
G
e
d
a
m
a
n
d
S
.
P
a
u
l
,
“
A
u
t
o
m
a
t
i
c
st
r
e
ss
d
e
t
e
c
t
i
o
n
u
si
n
g
w
e
a
r
a
b
l
e
s
e
n
so
r
s
a
n
d
mac
h
i
n
e
l
e
a
r
n
i
n
g
:
a
r
e
v
i
e
w
,
”
i
n
2
0
2
0
1
1
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
i
n
g
,
C
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
N
e
t
w
o
rki
n
g
T
e
c
h
n
o
l
o
g
i
e
s
(
I
C
C
C
N
T
)
,
J
u
l
.
2
0
2
0
,
p
p
.
1
–
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
C
C
N
T
4
9
2
3
9
.
2
0
2
0
.
9
2
2
5
6
9
2
.
[
2
9
]
R
.
K
r
i
s
h
n
a
V
a
n
a
k
a
ma
mi
d
i
,
L
.
R
a
ma
l
i
n
g
a
m,
N
.
A
b
i
r
a
m
i
,
S
.
P
r
i
y
a
n
k
a
,
C
.
S
.
K
u
mar,
a
n
d
S
.
M
u
r
u
g
a
n
,
“
I
o
T
s
e
c
u
r
i
t
y
b
a
s
e
d
o
n
mac
h
i
n
e
l
e
a
r
n
i
n
g
,
”
i
n
2
0
2
3
S
e
c
o
n
d
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
on
S
m
a
r
t
T
e
c
h
n
o
l
o
g
i
e
s
F
o
r
S
m
a
rt
N
a
t
i
o
n
(
S
m
a
r
t
T
e
c
h
C
o
n
)
,
A
u
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
P
r
ed
ictive
mo
d
elin
g
fo
r
h
ea
lth
ca
r
e
w
o
r
ke
r
w
e
ll
-
b
ein
g
w
ith
clo
u
d
…
(
Mu
t
h
u
ka
th
a
n
R
a
jen
d
r
a
n
S
u
d
h
a
)
1227
2
0
2
3
,
p
p
.
6
8
3
–
6
8
7
,
d
o
i
:
1
0
.
1
1
0
9
/
S
ma
r
t
Te
c
h
C
o
n
5
7
5
2
6
.
2
0
2
3
.
1
0
3
9
1
7
2
7
.
[
3
0
]
T
.
R
.
S
a
r
a
v
a
n
a
n
,
A
.
R
.
R
a
t
h
i
n
a
m
,
J
.
L
e
n
i
n
,
A
.
K
o
m
a
t
h
i
,
B
.
B
h
a
r
a
t
h
i
,
a
n
d
S
.
M
u
r
u
g
a
n
,
“
R
e
v
o
l
u
t
i
o
n
i
z
i
n
g
c
l
o
u
d
c
o
m
p
u
t
i
n
g
:
e
v
a
l
u
a
t
i
n
g
t
h
e
i
n
f
l
u
e
n
c
e
o
f
b
l
o
c
k
c
h
a
i
n
a
n
d
c
o
n
s
e
n
s
u
s
a
l
g
o
r
i
t
h
m
s
,
”
i
n
2
0
2
3
3
r
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
S
m
a
r
t
G
e
n
e
r
a
t
i
o
n
C
o
m
p
u
t
i
n
g
,
C
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
N
e
t
w
o
r
k
i
n
g
(
S
M
A
R
T
G
E
N
C
O
N
)
,
D
e
c
.
2
0
2
3
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
S
M
A
R
T
G
E
N
C
O
N
6
0
7
5
5
.
2
0
2
3
.
1
0
4
4
2
0
0
8
.
[
3
1
]
C
.
C
.
S
e
k
h
a
r
,
V
.
V
,
K
.
V
i
j
a
y
a
l
a
k
sh
mi
,
M
.
B
.
S
a
h
a
a
i
,
A
.
S
.
R
a
o
,
a
n
d
S
.
M
u
r
u
g
a
n
,
“
C
l
o
u
d
-
b
a
s
e
d
w
a
t
e
r
t
a
n
k
man
a
g
e
me
n
t
a
n
d
c
o
n
t
r
o
l
s
y
st
e
m,
”
i
n
2
0
2
3
S
e
c
o
n
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
on
S
m
a
r
t
T
e
c
h
n
o
l
o
g
i
e
s
f
o
r
S
m
a
rt
N
a
t
i
o
n
(
S
m
a
rt
T
e
c
h
C
o
n
)
,
A
u
g
.
2
0
2
3
,
p
p
.
6
4
1
–
6
4
6
,
d
o
i
:
1
0
.
1
1
0
9
/
S
mart
Te
c
h
C
o
n
5
7
5
2
6
.
2
0
2
3
.
1
0
3
9
1
7
3
0
.
[
3
2
]
K
.
K
a
r
t
h
i
k
a
,
S
.
D
h
a
n
a
l
a
k
s
h
mi
,
S
.
M
.
M
u
r
t
h
y
,
N
.
M
i
sh
r
a
,
S
.
S
a
s
i
k
a
l
a
,
a
n
d
S
.
M
u
r
u
g
a
n
,
“
R
a
sp
b
e
r
r
y
P
i
-
e
n
a
b
l
e
d
w
e
a
r
a
b
l
e
se
n
s
o
r
s
f
o
r
p
e
r
so
n
a
l
h
e
a
l
t
h
t
r
a
c
k
i
n
g
a
n
d
a
n
a
l
y
si
s
,
”
i
n
2
0
2
3
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
S
e
l
f
S
u
st
a
i
n
a
b
l
e
Art
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
S
y
st
e
m
s
(
I
C
S
S
AS
)
,
O
c
t
.
2
0
2
3
,
p
p
.
1
2
5
4
–
1
2
5
9
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
S
S
A
S
5
7
9
1
8
.
2
0
2
3
.
1
0
3
3
1
9
0
9
.
[
3
3
]
S
.
S
e
l
v
a
r
a
s
u
,
K
.
B
a
sh
k
a
r
a
n
,
K
.
R
a
d
h
i
k
a
,
S
.
V
a
l
a
r
m
a
t
h
y
,
a
n
d
S
.
M
u
r
u
g
a
n
,
“
I
o
T
-
e
n
a
b
l
e
d
me
d
i
c
a
t
i
o
n
saf
e
t
y
:
r
e
a
l
-
t
i
m
e
t
e
m
p
e
r
a
t
u
r
e
a
n
d
s
t
o
r
a
g
e
m
o
n
i
t
o
r
i
n
g
f
o
r
e
n
h
a
n
c
e
d
med
i
c
a
t
i
o
n
q
u
a
l
i
t
y
i
n
h
o
s
p
i
t
a
l
s,”
2
n
d
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
Au
t
o
m
a
t
i
o
n
,
C
o
m
p
u
t
i
n
g
a
n
d
Re
n
e
w
a
b
l
e
S
y
s
t
e
m
s,
I
C
A
C
R
S
2
0
2
3
-
Pr
o
c
e
e
d
i
n
g
s
,
p
p
.
2
5
6
–
2
6
1
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
A
C
R
S
5
8
5
7
9
.
2
0
2
3
.
1
0
4
0
5
2
1
2
.
B
IOG
R
A
PHI
E
S
OF
A
U
T
HO
R
S
Mu
th
u
k
a
th
a
n
Ra
je
n
d
r
a
n
S
u
d
h
a
re
c
e
iv
e
d
th
e
P
h
.
D
.
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
Un
iv
e
rsit
y
o
f
M
a
d
ra
s
i
n
2
0
2
2
.
S
h
e
re
c
e
iv
e
d
t
h
e
m
a
ste
r’s
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
M
a
d
u
ra
i
Ka
m
a
rj
Un
iv
e
rsity
,
M
a
d
u
ra
i,
Tam
il
Na
d
u
,
I
n
d
ia
i
n
1
9
9
6
.
S
i
n
c
e
2
0
1
2
,
s
h
e
h
a
s
b
e
e
n
wo
r
k
in
g
a
s
a
n
a
ss
istan
t
p
r
o
fe
ss
o
r
in
t
h
e
De
p
a
rtme
n
t
of
C
o
m
p
u
ter
Ap
p
li
c
a
ti
o
n
s
a
t
th
e
S
RM
In
stit
u
te
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
(fo
rm
e
rly
k
n
o
w
n
a
s
S
RM
Un
iv
e
rsity
)
i
n
Ch
e
n
n
a
i
,
In
d
ia.
He
r
re
se
a
rc
h
fo
c
u
se
s
o
n
i
n
tern
e
t
o
f
th
i
n
g
s
(Io
T)
,
g
re
e
n
e
n
e
rg
y
i
n
c
lo
u
d
d
a
ta
c
e
n
ters
,
c
lo
u
d
a
n
d
m
o
b
il
e
c
lo
u
d
c
o
m
p
u
ti
n
g
,
a
n
d
a
rti
ficia
l
in
telli
g
e
n
c
e
(AI)
a
n
d
m
a
c
h
in
e
lea
rn
in
g
.
S
h
e
is
h
a
v
i
n
g
2
3
y
e
a
rs
tea
c
h
in
g
e
x
p
e
rien
c
e
in
th
e
d
e
p
a
rtme
n
t
o
f
c
o
m
p
u
ter
sc
ien
c
e
.
S
h
e
h
a
s
b
e
e
n
wo
rk
i
n
g
a
s
lec
tu
re
r
c
u
m
h
e
a
d
o
f
th
e
De
p
a
rtme
n
t
of
C
o
m
p
u
ter
S
c
i
e
n
c
e
in
N.
M
.
S
.
S
e
rm
a
th
a
i
Va
sa
n
Co
ll
e
g
e
f
o
r
wo
m
e
n
,
M
a
d
u
ra
i,
I
n
d
ia.
S
h
e
is
a
l
ifetime
m
e
m
b
e
r
o
f
t
h
e
in
tern
a
ti
o
n
a
l
a
ss
o
c
iatio
n
o
f
e
n
g
i
n
e
e
rs
(IAENG
)
sin
c
e
2
0
1
8
.
S
h
e
h
a
s
p
u
b
li
sh
e
d
1
6
a
rti
c
les
in
p
e
e
r
re
v
iew
e
d
in
tern
a
ti
o
n
a
l
j
o
u
r
n
a
ls
a
n
d
p
re
se
n
ted
1
2
p
a
p
e
rs
in
in
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
su
d
h
a
m
2
@s
r
m
ist.
e
d
u
.
i
n
.
G
n
a
n
a
m
u
th
u
B
a
i
H
e
m
a
M
a
li
n
i
re
c
e
iv
e
d
t
h
e
P
h
.
D
.
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
Un
iv
e
rsit
y
o
f
M
a
d
ra
s
i
n
2
0
2
3
.
S
h
e
re
c
e
iv
e
d
th
e
m
a
ste
r’s
d
e
g
r
e
e
in
c
o
m
p
u
ter
a
p
p
li
c
a
ti
o
n
s
fro
m
M
a
n
o
m
a
n
a
iam
S
u
n
d
a
ra
n
a
r
Un
iv
e
rsit
y
,
Ti
r
u
n
e
l
v
e
li
,
Tam
il
Na
d
u
,
I
n
d
ia
i
n
2
0
0
2
.
S
in
c
e
2
0
0
9
,
sh
e
h
a
s
b
e
e
n
wo
r
k
in
g
a
s
a
n
a
ss
istan
t
p
r
o
fe
ss
o
r
i
n
t
h
e
d
e
p
a
rtme
n
t
o
f
c
o
m
p
u
ter
a
p
p
li
c
a
ti
o
n
s
a
t
th
e
S
h
rima
th
i
D
e
v
k
u
n
v
a
r
Na
n
a
lal
Bh
a
tt
Va
ish
n
a
v
Co
l
leg
e
fo
r
wo
m
e
n
in
Ch
e
n
n
a
i,
I
n
d
ia.
He
r
re
se
a
rc
h
fo
c
u
se
s o
n
ima
g
e
p
ro
c
e
ss
in
g
a
n
d
m
a
c
h
in
e
lea
rn
in
g
.
S
h
e
is h
a
v
in
g
1
7
y
e
a
rs
tea
c
h
in
g
e
x
p
e
rien
c
e
in
th
e
De
p
a
rtme
n
t
of
Co
m
p
u
ter
S
c
i
e
n
c
e
.
S
h
e
h
a
s
p
u
b
li
sh
e
d
4
a
rti
c
les
in
p
e
e
r
re
v
iew
e
d
in
tern
a
ti
o
n
a
l
jo
u
r
n
a
ls
a
n
d
p
re
se
n
ted
3
p
a
p
e
rs
in
i
n
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
g
b
h
m
a
li
n
i@y
a
h
o
o
.
c
o
.
i
n
.
Ra
n
g
a
sa
m
y
S
a
n
k
a
r
re
c
e
iv
e
d
B.
E.
d
e
g
re
e
in
e
lec
tri
c
a
l
a
n
d
e
lec
tro
n
ics
e
n
g
in
e
e
rin
g
fro
m
G
o
v
e
rn
m
e
n
t
C
o
ll
e
g
e
of
E
n
g
i
n
e
e
rin
g
,
Ti
ru
n
e
lv
e
l
i
a
n
d
M
.
E
.
d
e
g
re
e
in
c
o
n
tro
l
a
n
d
i
n
stru
m
e
n
tati
o
n
fr
o
m
An
n
a
Un
iv
e
rsity
,
CEG
,
Ch
e
n
n
a
i
in
1
9
9
5
a
n
d
2
0
0
1
re
sp
e
c
ti
v
e
ly
.
He
re
c
e
iv
e
d
th
e
P
h
.
D.
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
i
n
e
e
rin
g
fr
o
m
S
a
t
h
y
a
b
a
m
a
In
stit
u
te
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
C
h
e
n
n
a
i
in
2
0
1
2
.
H
e
h
a
s
2
4
y
e
a
rs
o
f
w
o
rk
e
x
p
e
rien
c
e
in
th
e
f
ield
o
f
tea
c
h
in
g
fro
m
v
a
rio
u
s rep
u
ted
a
c
a
d
e
m
ic o
rg
a
n
iza
ti
o
n
s a
c
ro
ss
Tam
il
Na
d
u
,
I
n
d
ia,
si
n
c
e
th
e
y
e
a
r
o
f
1
9
9
6
.
He
h
a
s
a
lso
p
u
b
li
sh
e
d
h
is
re
se
a
rc
h
p
a
p
e
rs
in
v
a
rio
u
s
re
p
u
te
d
S
c
o
p
u
s
a
n
d
S
CI
j
o
u
r
n
a
ls.
He
is
c
u
rre
n
tl
y
wo
r
k
in
g
a
s
p
ro
fe
ss
o
r
i
n
Ch
e
n
n
a
i
In
sti
tu
te
o
f
Tec
h
n
o
lo
g
y
,
Ch
e
n
n
a
i.
His
re
se
a
rc
h
a
re
a
is
p
o
we
r
e
lec
tro
n
ics
a
n
d
d
riv
e
s
.
He
is
th
e
li
fe
m
e
m
b
e
r
o
f
In
d
ian
so
c
iety
fo
r
tec
h
n
ica
l
e
d
u
c
a
ti
o
n
,
a
n
d
o
th
e
r
p
ro
fe
ss
io
n
a
l
so
c
ieties
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
:
sa
n
k
a
r3
6
7
3
@
y
a
h
o
o
.
c
o
m
.
Mu
r
u
g
a
a
b
o
o
p
a
th
y
M
y
th
il
y
h
o
l
d
s
a
d
o
c
to
ra
te
fro
m
An
n
a
Un
iv
e
rsity
,
with
b
a
c
h
e
lo
r'
s
a
n
d
m
a
ste
r'
s
d
e
g
re
e
s
sp
e
c
ializin
g
in
c
o
m
p
u
ter
sc
ien
c
e
a
n
d
e
n
g
i
n
e
e
rin
g
fr
o
m
Av
in
a
sh
il
i
n
g
a
m
De
e
m
e
d
Un
i
v
e
r
sity
a
n
d
G
o
v
e
rn
m
e
n
t
Co
ll
e
g
e
o
f
Tec
h
n
o
lo
g
y
,
Co
imb
a
to
re
,
Tam
il
Na
d
u
,
In
d
ia,
re
sp
e
c
ti
v
e
l
y
.
Cu
rre
n
tl
y
,
sh
e
se
rv
e
s
a
s
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
t
Ka
ru
n
y
a
In
stit
u
te
o
f
Tec
h
n
o
l
o
g
y
a
n
d
S
c
ien
c
e
s.
Wi
t
h
tw
o
d
e
c
a
d
e
s
o
f
e
x
p
e
ri
e
n
c
e
sp
a
n
n
i
n
g
b
o
t
h
i
n
d
u
str
y
a
n
d
a
c
a
d
e
m
ia,
h
e
r
e
x
p
e
rti
se
e
n
c
o
m
p
a
ss
e
s
so
ftwa
re
e
n
g
in
e
e
rin
g
,
d
e
sig
n
p
a
tt
e
rn
s,
p
ro
b
lem
-
so
lv
i
n
g
tec
h
n
i
q
u
e
s,
a
n
d
d
a
ta
sc
i
e
n
c
e
.
Dr.
M
y
t
h
il
y
h
a
s
c
o
n
tri
b
u
te
d
sig
n
if
ica
n
tl
y
t
o
h
e
r
fiel
d
with
o
v
e
r
3
0
p
u
b
li
c
a
ti
o
n
s
in
re
fe
re
e
d
in
tern
a
ti
o
n
a
l
jo
u
rn
a
ls
a
n
d
c
o
n
fe
re
n
c
e
p
ro
c
e
e
d
i
n
g
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
y
th
i
l
y
.
m
@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.