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Vo
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20
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1
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v
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.
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5782
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P
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se
(P
AD
)
is
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c
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o
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c
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k
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ircu
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,
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re
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o
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n
d
a
c
c
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e
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ti
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n
ti
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t
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ise
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),
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CG
),
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n
d
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h
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P
G
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to
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a
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lar
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e
a
lt
h
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LDF
m
e
a
su
re
s
m
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v
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d
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tes
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e
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d
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P
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c
a
p
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s
p
u
lse
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v
e
fo
rm
c
h
a
ra
c
teristics
.
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y
p
h
y
si
o
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o
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ica
l
fe
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tu
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s
su
c
h
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s
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w
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il
it
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,
p
u
lse
tra
n
sit
t
ime
,
a
n
d
h
e
m
o
d
y
n
a
m
ic
re
sp
o
n
se
s
a
re
e
x
trac
ted
a
n
d
a
n
a
ly
z
e
d
u
si
n
g
m
a
c
h
in
e
lea
rn
in
g
.
Ra
n
d
o
m
fo
re
st
a
n
d
XG
Bo
o
st
m
o
d
e
ls
a
re
e
m
p
lo
y
e
d
a
n
d
c
o
m
b
in
e
d
u
sin
g
e
n
se
m
b
le
l
e
a
rn
in
g
to
c
las
sify
in
d
i
v
i
d
u
a
ls
in
to
n
o
n
-
P
AD
,
m
o
d
e
ra
te
P
AD
,
a
n
d
s
e
v
e
re
P
AD
c
a
teg
o
ries
.
A
c
o
m
p
a
ra
ti
v
e
e
v
a
l
u
a
ti
o
n
sh
o
ws
t
h
a
t
th
e
e
n
se
m
b
le
m
o
d
e
l
d
e
li
v
e
rs su
p
e
ri
o
r
c
las
sifica
ti
o
n
a
c
c
u
ra
c
y
.
Th
is i
n
te
g
ra
ted
sy
ste
m
o
ffe
rs a fa
st,
re
li
a
b
le
sc
re
e
n
in
g
to
o
l
th
a
t
su
p
p
o
rts
e
a
rly
P
AD
d
e
tec
ti
o
n
a
n
d
i
n
t
e
rv
e
n
ti
o
n
.
By
c
o
m
b
in
i
n
g
m
u
lt
im
o
d
a
l
sig
n
a
l
a
n
a
l
y
sis
wit
h
m
a
c
h
in
e
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g
,
th
e
a
p
p
ro
a
c
h
e
n
h
a
n
c
e
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d
iag
n
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isio
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n
d
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s
a
sc
a
lab
le
s
o
lu
ti
o
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f
o
r
p
re
v
e
n
ti
v
e
c
a
rd
io
v
a
sc
u
lar ca
re
.
K
ey
w
o
r
d
s
:
E
lectr
o
ca
r
d
io
g
r
ap
h
y
L
aser
d
o
p
p
le
r
f
lo
wm
etr
y
Ma
ch
in
e
lear
n
in
g
Per
ip
h
er
al
ar
ter
ial
d
is
ea
s
e
Ph
o
to
p
leth
y
s
m
o
g
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ap
h
y
T
h
is i
s
a
n
o
p
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n
a
c
c
e
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a
rticle
u
n
d
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r th
e
CC B
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-
SA
li
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se
.
C
o
r
r
e
s
p
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A
uth
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r
:
So
b
h
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a
Mu
m
m
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Dep
ar
tm
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t o
f
C
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p
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Scie
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Facu
lty
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E
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Vela
g
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Sid
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h
ar
th
a
E
n
g
in
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r
in
g
C
o
lleg
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Vijay
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a,
5
2
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7
,
I
n
d
ia
E
m
ail:
s
o
b
h
an
a@
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s
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h
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.
ac
.
in
1.
I
NT
RO
D
UCT
I
O
N
Per
ip
h
er
al
ar
ter
ial
d
is
ea
s
e
(
P
AD)
,
a
wid
esp
r
ea
d
v
ascu
lar
co
n
d
itio
n
p
r
im
ar
ily
af
f
ec
tin
g
th
e
lo
wer
ex
tr
em
ities
,
im
p
ac
ts
o
v
er
2
0
0
m
illi
o
n
p
eo
p
le
wo
r
ld
wid
e
[
1
]
.
Prim
ar
ily
ca
u
s
ed
b
y
ath
er
o
s
cler
o
s
is
,
PAD
h
as
b
ec
o
m
e
a
m
ajo
r
p
u
b
lic
h
ea
lt
h
co
n
ce
r
n
d
u
e
to
its
r
is
in
g
p
r
ev
alen
ce
,
d
r
iv
en
b
y
ag
in
g
p
o
p
u
latio
n
s
an
d
r
is
k
f
ac
to
r
s
s
u
ch
as
d
iab
etes,
m
eta
b
o
lic
ab
n
o
r
m
alities
,
an
d
to
b
ac
co
u
s
e
[
2
]
.
I
n
ad
v
a
n
ce
d
s
tag
e
s
,
PAD
ca
n
lead
to
cr
itical
lim
b
is
ch
em
ia,
r
esu
lt
in
g
in
n
o
n
-
h
ea
lin
g
u
lcer
s
o
r
ev
en
lim
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am
p
u
tatio
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if
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t
u
n
tr
ea
ted
,
an
d
s
ig
n
if
ican
tly
in
cr
ea
s
es
th
e
r
is
k
o
f
s
er
io
u
s
ca
r
d
io
v
ascu
lar
c
o
m
p
licatio
n
s
lik
e
m
y
o
ca
r
d
ial
in
f
a
r
ctio
n
,
s
tr
o
k
e,
an
d
o
v
er
all
m
o
r
tality
[
3
]
.
Desp
ite
its
s
ev
er
ity
,
PAD
r
em
ain
s
wid
ely
u
n
d
e
r
d
iag
n
o
s
ed
,
p
a
r
ticu
lar
ly
in
th
e
ea
r
ly
s
tag
es,
d
u
e
to
th
e
lim
ited
s
e
n
s
itiv
ity
o
f
th
e
an
k
le
b
r
ac
h
ia
l
in
d
ex
(
AB
I
)
,
wh
ich
is
wid
ely
r
eg
ar
d
e
d
as
th
e
s
tan
d
ar
d
s
cr
ee
n
in
g
to
o
l
esp
ec
ially
in
p
atien
ts
with
d
iab
ete
s
-
r
elate
d
ar
ter
ial
ca
lcif
icatio
n
[
4
]
.
C
o
n
v
en
tio
n
al
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
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&
C
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m
p
E
n
g
I
SS
N:
2088
-
8
7
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P
r
ed
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n
o
f p
erip
h
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l a
r
teri
a
l d
is
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s
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th
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o
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in
va
s
i
ve
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ia
g
n
o
s
tic
a
p
p
r
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h
(
S
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h
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n
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Mu
mma
n
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)
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s
tatis
t
ical
ap
p
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d
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p
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cies
b
etwe
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k
f
ac
to
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s
,
lead
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to
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ed
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ce
d
p
r
ed
ictiv
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p
er
f
o
r
m
a
n
ce
.
T
h
is
s
tu
d
y
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d
r
ess
es
th
e
f
o
llo
win
g
q
u
esti
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n
:
C
an
a
m
u
ltimo
d
al
ap
p
r
o
ac
h
th
at
i
n
t
eg
r
ates
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tr
o
ca
r
d
io
g
r
ap
h
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E
C
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,
p
h
o
to
p
leth
y
s
m
o
g
r
ap
h
y
(
PPG
)
,
an
d
laser
d
o
p
p
ler
f
lo
wm
etr
y
(
L
DF
)
s
ig
n
als
with
m
ac
h
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e
lear
n
i
n
g
t
ec
h
n
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es
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h
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ce
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r
l
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ete
ctio
n
an
d
s
ev
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ity
class
if
icatio
n
o
f
PAD
co
m
p
ar
ed
to
co
n
v
en
tio
n
al
d
iag
n
o
s
tic
m
eth
o
d
s
?
R
ec
en
t
ad
v
an
ce
m
en
ts
in
n
o
n
-
in
v
asiv
e
d
iag
n
o
s
tic
tech
n
o
l
o
g
ies
o
f
f
er
p
r
o
m
is
in
g
s
o
lu
tio
n
s
to
th
es
e
ch
allen
g
es.
E
C
G,
a
r
o
u
tin
e
clin
ical
to
o
l,
p
r
o
v
id
es
in
s
ig
h
ts
in
to
h
ea
r
t
r
h
y
th
m
an
d
v
ar
iab
ilit
y
,
ai
d
in
g
ca
r
d
io
v
ascu
lar
r
is
k
ass
ess
m
e
n
t
[
5
]
.
PP
G,
wid
ely
u
s
ed
in
p
u
ls
e
o
x
im
eter
s
,
is
an
af
f
o
r
d
ab
le
an
d
p
o
r
tab
le
m
eth
o
d
f
o
r
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atin
g
v
ascu
la
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h
ea
lth
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u
itab
le
f
o
r
in
te
g
r
ati
o
n
in
to
wea
r
ab
le
d
ev
ices
[
6
]
,
[
7
]
.
L
DF
m
ea
s
u
r
es
s
k
in
b
lo
o
d
p
er
f
u
s
io
n
an
d
h
a
s
s
h
o
wn
h
ig
h
s
en
s
itiv
ity
in
d
etec
tin
g
co
m
p
r
o
m
is
ed
lo
wer
-
lim
b
cir
cu
latio
n
,
p
ar
ticu
lar
ly
in
h
ig
h
-
r
is
k
g
r
o
u
p
s
s
u
ch
as
h
em
o
d
ialy
s
is
p
atien
ts
[
8
]
.
Ma
c
h
in
e
lear
n
in
g
(
ML
)
en
h
a
n
ce
s
th
ese
to
o
ls
b
y
id
en
tify
in
g
in
t
r
icate
,
n
o
n
lin
ea
r
d
ata
p
atter
n
s
th
at
co
n
v
en
tio
n
al
m
o
d
els
m
is
s
[
1
]
.
Prio
r
s
tu
d
ies
d
em
o
n
s
tr
ate
th
at
ML
-
d
r
iv
e
n
an
aly
s
es
o
f
elec
tr
o
n
ic
h
ea
lth
r
ec
o
r
d
s
an
d
PP
G
d
ata
o
u
tp
er
f
o
r
m
tr
ad
itio
n
al
m
eth
o
d
s
in
PAD
p
r
ed
ictio
n
[
9
]
.
T
ec
h
n
iq
u
es
f
o
r
d
im
e
n
s
io
n
ality
r
ed
u
ctio
n
,
s
u
ch
as
p
r
in
cip
al
co
m
p
o
n
en
t
an
aly
s
is
(
PC
A)
,
h
elp
r
etain
th
e
m
o
s
t sig
n
if
ican
t v
ar
ian
ce
in
th
e
d
ataset
wh
ile
r
ed
u
cin
g
th
e
n
u
m
b
er
o
f
f
ea
tu
r
es
.
[
1
0
]
Similar
ly
,
e
n
s
em
b
le
m
eth
o
d
s
lik
e
r
an
d
o
m
f
o
r
est
an
d
XGBo
o
s
t
en
h
an
ce
m
o
d
el
ac
c
u
r
ac
y
an
d
r
ed
u
ce
t
h
e
r
is
k
o
f
o
v
er
f
itti
n
g
.
[
1
1
]
.
T
h
is
s
tu
d
y
ad
d
r
ess
es
th
ese
g
ap
s
b
y
p
r
o
p
o
s
in
g
a
n
o
v
el,
n
o
n
-
in
v
asiv
e
d
iag
n
o
s
tic
f
r
a
m
e
wo
r
k
th
at
s
y
n
er
g
is
tically
co
m
b
in
es
L
DF,
E
C
G,
an
d
PP
G
s
ig
n
als
to
as
s
ess
m
icr
o
v
ascu
lar
b
lo
o
d
f
lo
w,
ca
r
d
iac
d
y
n
am
ics,
an
d
v
ascu
lar
h
ea
lth
.
Ph
y
s
io
lo
g
ical
f
ea
tu
r
es,
i
n
clu
d
in
g
b
lo
o
d
f
lo
w
v
a
r
iab
ilit
y
,
p
u
ls
e
tr
an
s
it
tim
e,
an
d
h
em
o
d
y
n
am
ic
r
esp
o
n
s
es,
ar
e
ex
tr
ac
ted
an
d
an
aly
ze
d
u
s
in
g
an
en
s
em
b
le
m
ac
h
in
e
lear
n
in
g
m
o
d
el
co
m
p
r
is
in
g
r
an
d
o
m
f
o
r
est
an
d
XGBo
o
s
t
alg
o
r
ith
m
s
,
o
p
tim
ized
v
ia
Gr
i
d
Sear
ch
C
V
to
class
if
y
PAD
s
ev
er
ity
in
to
No
n
-
PAD,
Mo
d
er
ate
PAD,
a
n
d
Sev
er
e
PAD
ca
teg
o
r
ies
with
9
3
%
ac
cu
r
ac
y
.
T
o
m
a
x
im
ize
clin
ical
u
tili
ty
,
th
e
m
o
d
el
is
d
ep
lo
y
ed
t
h
r
o
u
g
h
a
Flas
k
-
b
ased
web
a
p
p
licatio
n
,
en
ab
lin
g
r
ap
id
,
u
s
er
-
f
r
ien
d
ly
PAD
s
cr
ee
n
in
g
in
d
iv
er
s
e
h
ea
lth
ca
r
e
s
ettin
g
s
.
T
h
is
ap
p
r
o
ac
h
f
ac
ilit
ates
ea
r
ly
d
etec
tio
n
,
s
u
p
p
o
r
ts
p
r
ev
en
tiv
e
ca
r
e,
an
d
p
av
es
th
e
way
f
o
r
p
er
s
o
n
alize
d
m
an
ag
e
m
en
t
o
f
PAD,
u
ltima
tely
aim
in
g
to
r
e
d
u
ce
its
clin
ical
an
d
ec
o
n
o
m
ic
b
u
r
d
en
.
Acc
o
r
d
in
g
to
p
r
i
o
r
r
esear
ch
,
t
h
is
wo
r
k
is
o
n
e
o
f
th
e
ea
r
lies
t
attem
p
ts
to
co
m
b
in
e
E
C
G,
PP
G,
an
d
L
DF
s
ig
n
al
s
with
en
s
em
b
le
m
o
d
els
to
class
if
y
th
e
s
ev
er
ity
o
f
PAD
.
T
h
is
in
teg
r
atio
n
o
f
f
er
s
a
n
o
v
el,
n
o
n
-
in
v
asiv
e,
an
d
ac
cu
r
ate
d
iag
n
o
s
tic
f
r
am
ewo
r
k
f
o
r
e
ar
ly
d
etec
tio
n
an
d
s
tr
atif
icatio
n
o
f
PAD.
T
h
e
o
b
jectiv
e
o
f
t
h
is
s
tu
d
y
is
t
o
p
r
o
p
o
s
e
a
n
o
n
-
in
v
asiv
e
d
ia
g
n
o
s
tic
f
r
am
ewo
r
k
f
o
r
th
e
ea
r
ly
d
etec
tio
n
an
d
s
tr
atif
icatio
n
o
f
PAD
s
ev
er
ity
.
T
h
is
is
ac
h
iev
ed
th
r
o
u
g
h
a
m
u
ltimo
d
al
m
eth
o
d
o
lo
g
y
th
at
in
co
r
p
o
r
ates
s
ig
n
als
f
r
o
m
elec
tr
o
ca
r
d
io
g
r
a
m
,
p
h
o
to
p
leth
y
s
m
o
g
r
ap
h
y
,
an
d
L
DF
.
E
s
s
en
tial
p
h
y
s
io
lo
g
ical
in
d
icato
r
s
s
u
ch
as
v
ar
iatio
n
s
in
b
lo
o
d
f
lo
w,
p
u
ls
e
tr
an
s
it
tim
es,
a
n
d
h
em
o
d
y
n
a
m
ic
r
esp
o
n
s
es
a
r
e
e
x
tr
ac
ted
a
n
d
p
r
o
ce
s
s
ed
.
T
h
ese
f
ea
tu
r
es
ar
e
s
u
b
s
eq
u
en
tly
ev
a
lu
ated
u
s
in
g
en
s
em
b
le
alg
o
r
it
h
m
s
,
n
am
ely
r
an
d
o
m
f
o
r
est
an
d
XGBo
o
s
t,
with
h
y
p
er
p
ar
am
eter
s
o
p
tim
ized
th
r
o
u
g
h
Gr
id
Sear
c
h
C
V.
T
h
e
r
esu
ltin
g
m
o
d
el
s
tr
atif
ies
PAD
in
to
th
r
ee
ca
teg
o
r
ies:
No
n
-
PAD,
Mo
d
er
ate
PAD,
an
d
Sev
er
e
PAD.
Fo
r
r
ea
l
-
w
o
r
ld
ap
p
licab
ilit
y
,
th
e
tr
ain
e
d
m
o
d
el
is
in
teg
r
ated
i
n
to
a
Flas
k
-
b
ased
web
p
latf
o
r
m
,
o
f
f
er
in
g
a
n
ac
ce
s
s
ib
le
an
d
r
ea
l
-
tim
e
s
cr
ee
n
in
g
to
o
l.
T
h
is
ap
p
r
o
ac
h
is
in
ten
d
ed
t
o
en
h
an
ce
d
iag
n
o
s
tic
p
r
ec
is
io
n
,
s
u
p
p
o
r
t
ea
r
ly
in
ter
v
e
n
tio
n
s
,
an
d
en
ab
le
in
d
iv
i
d
u
alize
d
m
a
n
ag
em
en
t
s
tr
ateg
ies
f
o
r
PAD.
T
h
e
s
tr
u
ctu
r
e
o
f
th
is
p
ap
er
i
s
o
r
g
an
ized
as:
s
ec
tio
n
2
d
is
cu
s
s
es
th
e
s
tate
-
of
-
th
e
-
ar
t
r
esear
ch
an
d
ex
is
tin
g
m
eth
o
d
o
lo
g
ies
r
elate
d
to
th
e
d
iag
n
o
s
is
o
f
PAD.
Se
ctio
n
3
o
u
tlin
es
th
e
id
en
tifie
d
r
esear
ch
g
ap
s
alo
n
g
with
th
e
m
ain
co
n
tr
ib
u
tio
n
s
o
f
th
is
wo
r
k
.
Sectio
n
4
d
etails
th
e
ad
o
p
ted
m
eth
o
d
o
lo
g
y
a
n
d
th
e
d
ata
u
tili
ze
d
.
Sectio
n
5
d
is
cu
s
s
es
th
e
ex
p
er
i
m
en
tal
f
in
d
in
g
s
.
Fin
ally
,
s
ec
tio
n
6
c
o
n
clu
d
es
th
e
s
tu
d
y
a
n
d
s
u
g
g
ests
d
ir
ec
tio
n
s
f
o
r
f
u
tu
r
e
r
esear
c
h
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
Allen
et
a
l.
[
1
2
]
p
r
o
p
o
s
ed
a
d
ee
p
lear
n
in
g
a
p
p
r
o
ac
h
u
tili
zin
g
p
h
o
to
p
leth
y
s
m
o
g
r
a
p
h
y
(
DL
PP
G)
was
em
p
lo
y
ed
to
id
e
n
tify
PAD
th
r
o
u
g
h
th
e
a
n
aly
s
is
o
f
to
e
-
b
ased
PP
G
s
ig
n
als.
T
h
e
o
b
jectiv
e
was
to
ev
alu
ate
th
e
ef
f
ec
tiv
en
ess
o
f
a
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
,
s
p
ec
if
ica
lly
Alex
Net
with
tr
an
s
f
er
le
ar
n
in
g
,
ap
p
lied
to
co
n
tin
u
o
u
s
wav
elet
tr
an
s
f
o
r
m
(
C
W
T
)
s
p
ec
tr
o
g
r
am
s
.
T
h
e
m
o
d
el
ac
h
iev
ed
8
6
.
6
%
s
en
s
itiv
ity
,
9
0
.
2
%
s
p
ec
if
icity
,
an
d
8
8
.
9
%
ac
cu
r
a
cy
with
a
C
o
h
en
’
s
Kap
p
a
o
f
0
.
7
6
u
s
in
g
5
-
f
o
ld
c
r
o
s
s
-
v
alid
a
tio
n
.
T
h
is
ap
p
r
o
ac
h
r
eq
u
ir
es
m
in
im
al
s
ig
n
al
p
r
e
p
r
o
ce
s
s
in
g
an
d
p
r
i
o
r
itizes
to
e
PP
G,
wh
ich
is
m
o
r
e
clin
ically
r
elev
an
t
f
o
r
PAD
d
etec
tio
n
th
an
f
in
g
er
-
b
ased
s
ig
n
als.
T
h
e
s
tu
d
y
h
i
g
h
lig
h
te
d
ch
allen
g
es
s
u
ch
as
m
a
n
ag
in
g
m
o
v
em
en
t
ar
tifa
cts
an
d
s
ig
n
al
n
o
is
e.
I
t
also
n
o
ted
th
at
th
e
d
ataset
was
n
o
t
f
u
lly
b
alan
ce
d
an
d
ce
r
tain
h
ea
lth
f
ac
to
r
s
lik
e
d
iab
etes
wer
e
n
o
t in
co
r
p
o
r
ated
.
Kim
et
a
l.
[
1
3
]
ex
p
lo
r
ed
PAD
d
etec
tio
n
an
d
s
ev
er
ity
ass
ess
m
en
t
u
s
in
g
d
ee
p
lear
n
in
g
o
n
ar
ter
ial
p
u
ls
e
wav
ef
o
r
m
s
.
A
s
y
n
th
eti
c
d
ataset
f
r
o
m
a
tr
an
s
m
is
s
io
n
lin
e
m
o
d
el
s
im
u
lated
v
ar
io
u
s
PAD
s
ev
er
ities
.
B
r
ac
h
ial
an
d
an
k
le
wav
ef
o
r
m
s
wer
e
an
aly
ze
d
u
s
in
g
a
m
o
d
if
ied
Alex
Net
C
NN,
ac
h
iev
in
g
9
7
%
s
en
s
itiv
ity
,
9
9
%
s
p
ec
if
icity
,
a
n
d
ac
c
u
r
a
cy
—
s
u
r
p
ass
in
g
th
e
tr
a
d
itio
n
al
AB
I
m
eth
o
d
.
T
h
is
a
p
p
r
o
ac
h
b
etter
ca
p
tu
r
e
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
.
6
,
Decem
b
e
r
20
25
:
5
7
8
2
-
5
7
9
1
5784
wav
ef
o
r
m
m
o
r
p
h
o
lo
g
y
a
n
d
in
d
iv
id
u
al
v
ar
iab
ilit
y
.
Key
ch
allen
g
es
in
clu
d
ed
u
s
e
o
f
v
ir
t
u
al
d
ata
an
d
lim
ite
d
r
ea
l
-
wo
r
ld
g
e
n
er
aliza
tio
n
.
T
h
e
s
tu
d
y
h
ig
h
lig
h
ts
d
ee
p
lear
n
in
g
'
s
p
o
ten
tial
f
o
r
ac
cu
r
ate,
n
o
n
-
i
n
v
asiv
e
PAD
s
cr
ee
n
in
g
,
with
f
u
tu
r
e
ef
f
o
r
ts
f
o
cu
s
ed
o
n
clin
ical
v
alid
atio
n
a
n
d
lo
ca
lizatio
n
.
Mc
B
an
e
et
a
l.
[
1
4
]
i
n
tr
o
d
u
ce
d
a
m
o
d
el
u
tili
zin
g
t
h
e
i
n
ce
p
tio
n
t
im
e
ar
c
h
itectu
r
e
to
d
etec
t
P
AD
f
r
o
m
r
esti
n
g
ar
ter
ial
D
o
p
p
ler
wav
e
f
o
r
m
s
.
T
r
ain
ed
o
n
d
ata
f
r
o
m
3
4
3
2
p
atien
ts
an
d
v
alid
ated
o
n
1
5
1
,
th
e
m
o
d
el
p
r
ed
icted
a
b
n
o
r
m
al
AB
I
v
al
u
e
s
with
h
ig
h
ac
cu
r
ac
y
(
r
est
AB
I
:
0
.
8
9
,
AUC
0
.
9
5
; p
o
s
tex
er
ci
s
e
AB
I
:
0
.
8
5
–
0
.
8
9
)
.
W
h
ile
th
e
m
eth
o
d
r
e
d
u
ce
s
th
e
n
ee
d
f
o
r
ex
e
r
cise
test
in
g
,
it
d
ep
en
d
s
o
n
h
ig
h
-
q
u
ality
wa
v
ef
o
r
m
ac
q
u
is
itio
n
.
L
im
itatio
n
s
in
clu
d
e
e
x
clu
s
io
n
o
f
ce
r
tain
p
atien
t
g
r
o
u
p
s
an
d
lim
ited
g
e
n
er
aliza
b
ilit
y
.
T
h
e
ap
p
r
o
ac
h
d
em
o
n
s
tr
ates stro
n
g
p
o
ten
tial
f
o
r
s
ca
lab
le,
n
o
n
-
in
v
asiv
e
PAD
s
cr
ee
n
in
g
.
Stan
s
b
y
et
a
l.
[
1
5
]
co
n
d
u
cte
d
a
p
r
o
s
p
ec
tiv
e
d
iag
n
o
s
tic
s
tu
d
y
t
o
ass
ess
th
e
ac
cu
r
ac
y
o
f
m
u
lti
-
s
ite
p
h
o
to
p
let
h
y
s
m
o
g
r
ap
h
y
(
MPPG)
in
id
en
tif
y
in
g
PAD
with
i
n
p
r
im
ar
y
ca
r
e
.
Usi
n
g
d
u
p
le
x
u
ltra
s
o
u
n
d
as
th
e
r
ef
er
en
ce
s
tan
d
ar
d
,
MPPG
d
em
o
n
s
tr
ated
a
s
en
s
itiv
ity
o
f
7
9
.
8
%
an
d
s
p
ec
if
icity
o
f
7
1
.
9
%,
co
m
p
ar
ab
le
to
th
e
tr
ad
itio
n
al
an
k
le
-
b
r
ac
h
ial
p
r
e
s
s
u
r
e
in
d
ex
(
AB
PI)
,
wh
ich
s
h
o
wed
8
0
.
2
%
s
en
s
itiv
ity
an
d
8
8
.
6
%
s
p
ec
if
icity
.
Un
lik
e
AB
PI,
M
PP
G
was
f
a
s
ter
,
au
to
m
ated
,
an
d
r
e
q
u
ir
ed
l
ess
o
p
er
ato
r
tr
ain
in
g
.
Ho
wev
er
,
th
e
s
tu
d
y
f
ac
ed
ch
allen
g
es
s
u
ch
as
a
n
8
.
4
%
t
est
f
ailu
r
e
r
ate
d
u
e
to
s
ig
n
al
q
u
ality
an
d
p
r
o
to
ty
p
e
d
e
v
ice
lim
itatio
n
s
.
Desp
ite
th
ese
co
n
s
tr
ain
ts
,
th
e
r
esear
c
h
h
ig
h
lig
h
ts
MPPG’
s
p
o
ten
ti
al
as
a
s
ca
lab
le,
n
o
n
-
in
v
asiv
e
d
iag
n
o
s
tic
to
o
l
f
o
r
ea
r
ly
PAD
d
etec
tio
n
in
p
r
im
ar
y
ca
r
e
s
ettin
g
s
.
Fo
r
g
h
an
i
et
a
l.
[
1
6
]
p
r
o
p
o
s
ed
Dee
p
PAD,
a
n
o
v
el
d
ee
p
le
ar
n
in
g
f
r
am
ew
o
r
k
f
o
r
id
e
n
tif
y
in
g
PAD
u
s
in
g
Oscill
o
m
etr
ic
p
u
ls
e
wav
ef
o
r
m
s
r
ec
o
r
d
ed
at
d
if
f
e
r
en
t
cu
f
f
p
r
ess
u
r
es.
T
h
e
s
y
s
tem
em
p
lo
y
e
d
an
atten
tio
n
-
en
h
a
n
ce
d
b
i
d
ir
ec
tio
n
al
L
STM
m
o
d
el
to
an
aly
ze
r
aw
Oscill
o
m
etr
ic
p
u
ls
es
an
d
ex
tr
ac
ted
f
ea
tu
r
es.
E
v
alu
ated
o
n
d
ata
f
r
o
m
3
3
i
n
d
iv
id
u
als,
th
e
m
o
d
el
ac
h
iev
ed
u
p
to
9
4
.
8
%
ac
cu
r
ac
y
,
9
0
.
0
%
s
en
s
itiv
ity
,
an
d
9
7
.
4
%
s
p
ec
if
icity
,
o
u
t
p
er
f
o
r
m
in
g
th
e
co
n
v
en
tio
n
al
AB
I
an
d
a
g
e
n
etic
alg
o
r
ith
m
-
b
a
s
ed
n
eu
r
al
n
etwo
r
k
(
GA
-
NN)
.
Desp
ite
it
s
h
ig
h
p
er
f
o
r
m
a
n
ce
,
lim
itatio
n
s
in
clu
d
e
d
a
s
m
all
s
am
p
le
s
ize
an
d
lac
k
o
f
PAD
s
ev
er
ity
class
if
icatio
n
.
So
n
d
er
m
an
et
a
l.
[
1
7
]
in
tr
o
d
u
ce
d
a
m
ac
h
i
n
e
lear
n
in
g
m
o
d
el
aim
ed
at
id
en
tif
y
in
g
in
d
iv
id
u
als
at
h
ig
h
r
is
k
f
o
r
p
e
r
ip
h
er
al
ar
ter
y
d
is
ea
s
e
b
y
an
al
y
zin
g
elec
tr
o
n
i
c
h
ea
lth
r
ec
o
r
d
(
E
HR
)
d
ata.
Un
lik
e
t
r
ad
itio
n
a
l
s
cr
ee
n
in
g
ap
p
r
o
ac
h
es,
th
is
m
eth
o
d
co
m
b
i
n
ed
AB
I
m
ea
s
u
r
em
en
ts
with
a
b
r
o
ad
s
et
o
f
p
atien
t
f
ea
tu
r
es
to
im
p
r
o
v
e
p
r
ed
ictio
n
ac
cu
r
ac
y
.
T
h
e
r
esear
ch
e
r
s
ap
p
lied
a
r
an
d
o
m
f
o
r
est
alg
o
r
ith
m
to
s
e
lect
k
ey
v
ar
ia
b
les,
f
o
llo
wed
b
y
a
lo
g
is
tic
r
e
g
r
ess
io
n
m
o
d
el
t
o
class
if
y
PAD
r
is
k
.
T
h
e
m
o
d
el
s
h
o
wed
co
n
s
is
ten
t
p
er
f
o
r
m
an
ce
with
an
AUC
ar
o
u
n
d
0
.
6
8
ac
r
o
s
s
in
ter
n
al
an
d
ex
ter
n
al
d
atasets
,
an
d
s
lig
h
tly
h
ig
h
er
ac
cu
r
ac
y
(
AUC
0
.
7
2
)
o
n
a
n
atio
n
al
s
am
p
le,
o
u
t
p
er
f
o
r
m
in
g
s
im
p
ler
ag
e
-
b
ased
p
r
ed
ictio
n
s
.
Desp
ite
th
ese
s
tr
en
g
th
s
,
ch
allen
g
es
r
em
ain
in
h
an
d
lin
g
th
e
v
ar
iab
ilit
y
an
d
c
o
m
p
leten
ess
o
f
E
HR
d
ata.
L
i
m
itatio
n
s
in
clu
d
e
m
o
d
er
ate
p
r
ed
ictiv
e
p
o
wer
an
d
lack
o
f
v
alid
atio
n
in
r
ea
l
-
wo
r
ld
clin
ical
wo
r
k
f
lo
ws.
Fu
tu
r
e
r
esear
ch
co
u
ld
en
h
an
ce
m
o
d
el
r
o
b
u
s
tn
ess
an
d
ass
es
s
its
im
p
ac
t o
n
p
atien
t c
ar
e
.
3.
RE
S
E
ARCH
G
AP
S AN
D
P
RO
P
O
SE
D
CO
NT
RI
B
UT
I
O
NS
R
ec
en
t
s
tu
d
ies
[
1
2
]
–
[
1
7
]
o
n
n
o
n
-
in
v
asiv
e
PAD
d
etec
tio
n
r
el
y
o
n
s
in
g
le
m
o
d
alities
s
u
ch
as
P
PG
[
1
2
]
,
[
1
5
]
,
[
1
6
]
,
Do
p
p
ler
wav
e
f
o
r
m
s
[
1
4
]
,
o
r
E
HR
d
ata
[
1
7
]
,
lim
itin
g
th
eir
ab
ilit
y
to
ca
p
tu
r
e
PAD’
s
co
m
p
lex
m
icr
o
v
ascu
lar
,
ca
r
d
iac,
an
d
v
ascu
lar
d
y
n
am
ics.
Key
li
m
itatio
n
s
in
clu
d
e
s
m
all
s
am
p
le
s
izes
(
e.
g
.
,
3
3
in
d
iv
id
u
als
in
[
1
6
]
)
,
s
y
n
th
etic
d
atasets
with
p
o
o
r
r
ea
l
-
wo
r
ld
g
en
e
r
aliza
b
ilit
y
[
1
3
]
,
ab
s
en
ce
o
f
PAD
s
ev
er
ity
class
if
icatio
n
[
1
2
]
,
[
1
4
]
,
[
1
6
]
,
[
1
7
]
,
a
n
d
lack
o
f
s
ca
lab
le
d
e
p
lo
y
m
en
t
m
ec
h
a
n
is
m
s
[
1
4
]
,
[
1
5
]
.
T
h
e
p
r
o
p
o
s
ed
s
tu
d
y
ad
d
r
ess
es
th
ese
g
ap
s
b
y
in
teg
r
atin
g
L
DF,
E
C
G,
an
d
PP
G
s
ig
n
als
w
ith
in
an
en
s
em
b
le
m
ac
h
in
e
lear
n
in
g
f
r
am
ewo
r
k
(
r
a
n
d
o
m
f
o
r
est
an
d
XGBo
o
s
t)
,
ac
h
iev
in
g
9
3
%
ac
cu
r
ac
y
i
n
class
if
y
in
g
PAD
s
ev
er
ity
(
n
on
-
PAD,
m
o
d
er
ate
PAD,
s
ev
er
e
PAD)
o
n
a
r
o
b
u
s
t
1
,
0
0
0
s
am
p
le
d
at
aset
[
1
8
]
,
[
1
9
]
.
Dep
lo
y
ed
v
ia
a
Flas
k
-
b
ased
web
in
ter
f
ac
e,
th
is
ap
p
r
o
ac
h
o
f
f
er
s
a
s
ca
lab
le,
ac
cu
r
ate,
an
d
clin
i
ca
lly
ac
ce
s
s
ib
le
s
o
lu
tio
n
f
o
r
e
ar
ly
PAD
d
etec
tio
n
an
d
m
an
a
g
em
en
t,
a
d
v
an
ci
n
g
p
r
ev
en
tiv
e
ca
r
d
io
v
ascu
lar
ca
r
e.
4.
M
E
T
H
O
DO
L
O
G
Y
T
h
is
s
tu
d
y
p
r
esen
ts
a
r
o
b
u
s
t
class
if
icatio
n
f
r
am
ewo
r
k
aim
e
d
at
d
etec
tin
g
a
n
d
ass
ess
in
g
th
e
s
ev
er
ity
o
f
PAD
u
s
in
g
p
h
y
s
io
lo
g
ical
s
ig
n
als
an
d
en
s
em
b
le
m
ac
h
in
e
lear
n
in
g
.
T
h
e
m
et
h
o
d
o
lo
g
y
p
r
io
r
itizes
ac
cu
r
ac
y
,
in
ter
p
r
etab
ilit
y
,
an
d
e
f
f
ec
tiv
e
p
r
ep
r
o
ce
s
s
in
g
to
en
s
u
r
e
c
lin
ical
ap
p
licab
ilit
y
.
T
h
e
s
y
s
tem
lev
er
ag
es
an
en
s
em
b
le
class
if
icatio
n
m
o
d
el
in
teg
r
atin
g
r
a
n
d
o
m
f
o
r
est
an
d
XGBo
o
s
t
with
s
o
f
t
v
o
tin
g
,
en
ab
lin
g
m
u
lti
-
class
class
if
icatio
n
o
f
PAD
in
to
No
n
-
PAD,
Mo
d
er
ate
PAD,
an
d
Sev
er
e
PAD
ca
teg
o
r
ies.
T
h
e
m
eth
o
d
o
lo
g
y
is
d
etailed
in
th
e
f
o
llo
win
g
s
u
b
s
ec
tio
n
s
.
Data
ac
q
u
is
itio
n
an
d
p
r
ep
r
o
ce
s
s
in
g
s
tr
ateg
ie
s
ar
e
d
is
cu
s
s
ed
in
s
u
b
s
ec
tio
n
s
4
.
1
an
d
4
.
2
.
T
h
e
ar
ch
itectu
r
e
an
d
tr
ain
in
g
o
f
th
e
b
ase
class
if
ier
s
ar
e
d
escr
ib
ed
in
s
u
b
s
ec
tio
n
s
4
.
3
an
d
4
.
4
.
T
h
e
e
n
s
em
b
le
a
p
p
r
o
ac
h
is
o
u
tlin
ed
i
n
th
e
s
u
b
s
ec
tio
n
4
.
5
,
f
o
llo
wed
b
y
ev
al
u
atio
n
p
r
o
to
c
o
ls
in
s
u
b
s
ec
tio
n
4
.
6
.
Fig
u
r
e
1
illu
s
tr
ates th
e
co
m
p
lete
PAD
class
if
i
ca
tio
n
p
ip
elin
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
ictio
n
o
f p
erip
h
era
l a
r
teri
a
l d
is
ea
s
e
th
r
o
u
g
h
n
o
n
-
in
va
s
i
ve
d
ia
g
n
o
s
tic
a
p
p
r
o
a
c
h
(
S
o
b
h
a
n
a
Mu
mma
n
e
n
i
)
5785
Fig
u
r
e
1
.
Pro
p
o
s
ed
m
et
h
o
d
o
lo
g
y
f
o
r
PAD
c
lass
if
icatio
n
4
.
1
.
Da
t
a
c
o
llect
io
n a
nd
prepro
ce
s
s
ing
T
h
e
d
ata
co
llectio
n
a
n
d
p
r
ep
r
o
ce
s
s
in
g
p
h
ase,
was
co
n
d
u
cte
d
u
n
d
e
r
ca
r
ef
u
lly
co
n
tr
o
lled
c
o
n
d
itio
n
s
,
en
s
u
r
ed
th
e
in
teg
r
ity
an
d
r
ele
v
an
ce
o
f
th
e
d
ataset,
wh
ich
in
clu
d
es
ess
en
tial
p
h
y
s
io
lo
g
ical
s
ig
n
als
u
s
ed
f
o
r
th
e
class
if
icatio
n
o
f
PAD
.
T
wo
p
r
im
ar
y
s
o
u
r
ce
s
wer
e
co
n
s
id
er
ed
,
b
o
th
p
u
b
licly
ac
ce
s
s
ib
le.
T
h
e
f
ir
s
t
d
ataset,
o
b
tain
ed
f
r
o
m
Kag
g
le
[
1
8
]
,
f
o
cu
s
es
o
n
E
C
G
an
d
PP
G
s
ig
n
als
an
d
is
o
r
g
an
ized
in
to
r
ec
o
r
d
in
g
s
th
at
ca
p
tu
r
e
v
ar
io
u
s
ca
r
d
io
v
ascu
lar
co
n
d
i
tio
n
s
.
T
h
e
s
ec
o
n
d
d
ataset
c
o
n
s
is
ts
o
f
L
DF
m
ea
s
u
r
e
m
en
ts
s
o
u
r
ce
d
f
r
o
m
a
p
u
b
lis
h
ed
m
ed
ical
s
tu
d
y
[
1
9
]
,
wh
ich
p
r
o
v
id
es
m
icr
o
v
ascu
lar
b
lo
o
d
f
l
o
w
d
ata
f
o
r
b
o
th
h
ea
lt
h
y
in
d
iv
id
u
als
an
d
PAD
p
atien
ts
.
T
h
e
d
ataset
in
clu
d
es
h
ig
h
-
r
eso
lu
tio
n
L
DF
v
alu
es
in
d
icativ
e
o
f
tis
s
u
e
p
er
f
u
s
io
n
le
v
els.
T
o
en
s
u
r
e
th
e
r
elia
b
ilit
y
o
f
m
u
ltimo
d
al
s
ig
n
al
a
n
aly
s
is
,
E
C
G,
PP
G,
an
d
L
DF
d
ata
wer
e
c
o
m
b
in
ed
th
r
o
u
g
h
tim
e
s
y
n
ch
r
o
n
izatio
n
tech
n
i
q
u
es,
al
ig
n
in
g
th
em
to
a
co
m
m
o
n
tem
p
o
r
al
win
d
o
w.
T
h
is
en
ab
led
a
cc
u
r
ate
cr
o
s
s
-
s
ig
n
al
co
r
r
elatio
n
an
d
r
o
b
u
s
t
f
ea
tu
r
e
ex
tr
ac
tio
n
.
T
h
e
f
in
al
d
ataset
is
ca
teg
o
r
ized
in
to
th
r
ee
class
es
:
No
n
-
PAD,
Mo
d
er
ate
PAD,
an
d
Sev
e
r
e
PAD,
s
u
p
p
o
r
tin
g
ef
f
ec
tiv
e
class
if
icatio
n
o
f
PAD
s
ev
er
ity
.
4
.
2
.
Da
t
a
lo
a
din
g
a
nd
pro
ce
s
s
ing
T
h
e
d
ata
p
r
ep
r
o
ce
s
s
in
g
p
h
ase
b
eg
in
s
with
im
p
o
r
tin
g
th
e
PA
D
d
ataset,
wh
ich
in
clu
d
es
p
h
y
s
io
lo
g
ical
s
ig
n
als
s
u
ch
as
(
L
DF;
b
lo
o
d
f
lo
w
in
m
L
/m
in
)
,
PP
G,
an
d
E
C
G,
u
s
in
g
th
e
Pan
d
as
lib
r
a
r
y
f
o
r
ef
f
icien
t
d
ata
m
an
ip
u
latio
n
an
d
e
x
p
lo
r
atio
n
.
T
h
e
tar
g
et
lab
els
(
"
n
on
-
PA
D",
"
m
o
d
er
ate
PAD",
a
n
d
"
s
ev
er
e
PAD")
ar
e
en
co
d
ed
u
s
in
g
L
a
b
elE
n
co
d
er
to
en
ab
le
s
u
p
er
v
is
ed
lear
n
in
g
.
T
o
ca
p
tu
r
e
n
o
n
lin
ea
r
r
e
latio
n
s
h
ip
s
am
o
n
g
f
ea
tu
r
es,
a
s
ec
o
n
d
-
d
e
g
r
ee
p
o
ly
n
o
m
ial
ex
p
an
s
io
n
is
ap
p
lie
d
u
s
in
g
p
o
ly
n
o
m
ial.
Featu
r
es,
b
alan
cin
g
m
o
d
el
co
m
p
lex
ity
with
en
h
a
n
ce
d
f
e
atu
r
e
ex
p
r
ess
iv
en
ess
wh
ile
av
o
id
in
g
th
e
c
o
m
p
u
tatio
n
al
co
s
t
o
f
h
ig
h
er
-
d
e
g
r
ee
ter
m
s
.
Featu
r
e
s
tan
d
ar
d
izatio
n
is
th
en
a
p
p
lied
th
r
o
u
g
h
Stan
d
ar
d
Scaler
,
wh
ich
n
o
r
m
ali
ze
s
th
e
d
ata
to
ze
r
o
m
ea
n
an
d
u
n
it
v
ar
ian
ce
,
en
s
u
r
in
g
u
n
if
o
r
m
co
n
t
r
ib
u
tio
n
o
f
al
l
f
ea
tu
r
es
d
u
r
in
g
m
o
d
el
tr
ain
in
g
an
d
im
p
r
o
v
es
th
e
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
.
6
,
Decem
b
e
r
20
25
:
5
7
8
2
-
5
7
9
1
5786
co
n
v
er
g
en
ce
s
p
ee
d
an
d
s
tab
ilit
y
o
f
th
e
m
ac
h
in
e
lear
n
in
g
al
g
o
r
ith
m
s
.
T
o
f
u
r
th
er
o
p
tim
ize
th
e
f
ea
tu
r
e
s
et
an
d
r
ed
u
ce
r
e
d
u
n
d
an
cy
,
PC
A
was
ap
p
lied
,
as d
is
cu
s
s
ed
in
th
e
f
o
l
lo
win
g
s
u
b
s
ec
tio
n
.
4
.
2
.
1
.
P
rincipa
l
co
m
po
nent
a
na
ly
s
is
T
o
ad
d
r
ess
th
e
h
ig
h
d
im
en
s
io
n
ality
an
d
m
u
ltico
llin
ea
r
ity
in
tr
o
d
u
ce
d
b
y
p
o
ly
n
o
m
i
al
f
ea
tu
r
e
ex
p
an
s
io
n
,
PC
A
was
em
p
lo
y
e
d
to
co
m
p
r
ess
th
e
f
ea
tu
r
e
s
p
ac
e.
PC
A
tr
an
s
f
o
r
m
s
th
e
s
tan
d
ar
d
ized
f
ea
tu
r
e
s
p
ac
e
in
to
a
s
et
o
f
u
n
co
r
r
elate
d
p
r
i
n
cip
al
co
m
p
o
n
e
n
ts
th
at
ca
p
tu
r
e
th
e
m
ax
im
u
m
v
a
r
ian
ce
i
n
th
e
d
ataset,
th
er
e
b
y
s
im
p
lify
in
g
th
e
d
ataset
wh
ile
m
ain
tain
in
g
its
co
r
e
s
tr
u
ctu
r
al
ch
ar
ac
ter
is
tics
.
I
n
th
is
s
tu
d
y
,
co
m
p
o
n
en
ts
wer
e
r
etain
ed
s
u
ch
th
at
9
8
%
o
f
th
e
to
tal
v
ar
ian
ce
was
p
r
eser
v
ed
,
im
p
lem
en
ted
v
ia
PC
A(
_
=
0
.
9
8
)
.
T
h
is
s
tr
ateg
y
ef
f
ec
tiv
ely
m
in
im
izes
r
ed
u
n
d
a
n
cy
,
ac
ce
ler
ates
m
o
d
el
tr
ain
in
g
,
an
d
m
ain
tain
s
cr
itical
p
h
y
s
io
lo
g
ical
s
ig
n
al
p
atter
n
s
.
PC
A
was
s
elec
ted
o
v
er
alter
n
ativ
e
m
eth
o
d
s
lik
e
lin
ea
r
d
is
cr
im
in
an
t
an
aly
s
is
(
L
DA)
an
d
t
-
d
is
tr
ib
u
ted
s
to
ch
asti
c
n
eig
h
b
o
r
e
m
b
ed
d
in
g
(
t
-
SNE
)
d
u
e
to
its
u
n
s
u
p
er
v
is
ed
n
atu
r
e,
em
p
h
asis
o
n
v
ar
ian
ce
r
eten
tio
n
,
an
d
co
m
p
u
tatio
n
al
ef
f
icien
cy
f
o
r
c
o
n
tin
u
o
u
s
b
io
m
ed
ical
d
ata.
L
DA
was
ex
clu
d
ed
to
av
o
i
d
p
o
ten
tial
o
v
er
f
itti
n
g
to
class
l
ab
els,
wh
ile
t
-
SNE
was
co
n
s
i
d
er
ed
u
n
s
u
itab
le
g
iv
en
its
co
m
p
u
tatio
n
al
d
em
a
n
d
s
an
d
f
o
cu
s
o
n
d
ata
v
is
u
aliza
tio
n
r
ath
er
th
an
p
r
ed
ictiv
e
m
o
d
e
lin
g
.
Af
ter
o
p
tim
izin
g
th
e
f
ea
t
u
r
e
s
p
ac
e,
th
e
n
ex
t
s
tep
f
o
cu
s
ed
o
n
d
esig
n
in
g
m
ac
h
in
e
lear
n
in
g
m
o
d
els f
o
r
PAD
class
if
icatio
n
u
s
in
g
th
e
p
r
o
ce
s
s
ed
in
p
u
t sig
n
als.
4
.
3
.
M
o
del
c
re
a
t
io
n
T
h
e
m
o
d
el
d
ev
el
o
p
m
en
t
p
h
as
e
was
ce
n
ter
ed
o
n
estab
lis
h
in
g
a
class
if
icatio
n
f
r
am
ewo
r
k
t
o
id
en
tify
th
e
s
ev
er
ity
o
f
PAD,
ca
teg
o
r
ized
in
to
n
on
-
PAD,
m
o
d
er
a
te
PAD,
an
d
s
ev
er
e
PAD,
u
s
in
g
p
r
e
p
r
o
ce
s
s
ed
p
h
y
s
io
lo
g
ical
s
ig
n
als.
T
w
o
m
ac
h
in
e
lear
n
in
g
m
o
d
els
s
u
ch
as
r
an
d
o
m
f
o
r
est
a
n
d
XGBo
o
s
t
wer
e
s
elec
ted
d
u
e
to
th
eir
ef
f
ec
tiv
e
n
ess
in
m
an
ag
in
g
m
u
lti
-
class
class
if
icati
o
n
,
p
a
r
ticu
lar
ly
with
m
e
d
ical
d
atasets
.
R
an
d
o
m
f
o
r
est,
in
tr
o
d
u
ce
d
b
y
B
r
eim
an
,
is
an
en
s
em
b
le
m
eth
o
d
b
ased
o
n
d
ec
is
io
n
tr
ee
s
[
2
0
]
,
b
u
ild
s
n
u
m
er
o
u
s
d
ec
is
io
n
tr
ee
s
an
d
p
r
ed
icts
th
e
class
b
a
s
ed
o
n
th
e
m
ajo
r
ity
v
o
te
ac
r
o
s
s
th
ese
tr
ee
s
.
T
h
is
m
eth
o
d
is
p
ar
ticu
lar
ly
ef
f
ec
tiv
e
in
ca
p
tu
r
in
g
n
o
n
-
lin
ea
r
d
e
p
en
d
en
cies
with
in
d
iv
e
r
s
e
p
h
y
s
io
lo
g
ical
d
ata.
Fo
r
th
is
s
tu
d
y
,
r
an
d
o
m
Fo
r
est
was
f
in
e
-
tu
n
e
d
u
s
in
g
Gr
id
Sear
ch
C
V,
s
et
to
b
u
ild
4
0
0
tr
ee
s
,
with
a
m
ax
im
u
m
d
ep
t
h
o
f
ten
,
m
in
i
m
u
m
s
am
p
les
s
p
lit
o
f
two
,
an
d
b
ala
n
ce
d
class
w
eig
h
tin
g
to
ad
d
r
ess
class
im
b
alan
ce
an
d
im
p
r
o
v
e
g
en
e
r
aliza
tio
n
.
XG
B
o
o
s
t,
a
g
r
ad
ien
t
b
o
o
s
tin
g
-
b
ased
m
o
d
el,
s
eq
u
en
tially
co
n
s
tr
u
cts
tr
ee
s
to
co
r
r
ec
t
e
r
r
o
r
s
m
ad
e
b
y
p
r
io
r
o
n
es
an
d
in
co
r
p
o
r
ates
r
eg
u
la
r
izatio
n
to
r
ed
u
ce
o
v
er
f
itti
n
g
[
2
1
]
.
Fo
r
o
u
r
task
,
XGBo
o
s
t
was
co
n
f
ig
u
r
ed
with
a
lear
n
in
g
r
ate
o
f
0
.
1
,
m
ax
im
u
m
d
e
p
t
h
o
f
6
,
an
d
3
0
0
b
o
o
s
tin
g
r
o
u
n
d
s
,
u
s
in
g
a
m
u
lti
-
class
lo
g
-
lo
s
s
o
b
jectiv
e.
Hy
p
er
p
ar
a
m
eter
tu
n
in
g
was
also
p
er
f
o
r
m
ed
v
ia
Gr
id
Sear
c
h
C
V
to
en
h
an
ce
class
if
icatio
n
ac
cu
r
ac
y
.
All
in
p
u
t
f
ea
tu
r
es
wer
e
d
er
iv
ed
f
r
o
m
th
r
ee
p
h
y
s
io
lo
g
ical
s
ig
n
al
m
o
d
a
liti
es:
L
DF,
PP
G,
an
d
E
C
G.
Pre
p
r
o
ce
s
s
in
g
s
tep
s
in
clu
d
ed
la
b
el
en
c
o
d
in
g
,
p
o
ly
n
o
m
ial
f
ea
tu
r
e
ex
p
an
s
io
n
,
s
tan
d
ar
d
izatio
n
,
an
d
d
im
e
n
s
io
n
al
ity
r
ed
u
ctio
n
u
s
in
g
PC
A
to
im
p
r
o
v
e
lear
n
in
g
p
er
f
o
r
m
an
ce
.
O
n
ce
m
o
d
el
ar
ch
ite
ctu
r
es
an
d
h
y
p
er
p
ar
am
eter
s
w
er
e
f
in
alize
d
,
b
o
th
class
if
ier
s
wer
e
tr
ain
ed
in
d
ep
e
n
d
en
tly
o
n
th
e
r
ef
in
ed
d
ataset
4
.
4
.
M
o
del
t
ra
ini
ng
I
n
th
e
tr
ain
in
g
p
h
ase,
two
en
s
em
b
le
lear
n
in
g
alg
o
r
ith
m
s
r
a
n
d
o
m
f
o
r
est
an
d
XGBo
o
s
t
wer
e
u
s
ed
to
cr
ea
te
p
r
ed
ictiv
e
m
o
d
els.
E
ac
h
was
tr
ain
ed
in
d
ep
en
d
en
tl
y
o
n
a
p
r
e
p
r
o
ce
s
s
ed
an
d
d
im
en
s
io
n
ally
r
ed
u
ce
d
d
ataset.
T
h
e
r
an
d
o
m
f
o
r
est
al
g
o
r
ith
m
b
u
ild
s
an
en
s
em
b
le
o
f
d
ec
is
io
n
tr
ee
s
wh
o
s
e
co
m
b
i
n
ed
o
u
tp
u
t
en
h
a
n
ce
s
p
r
ed
ictio
n
p
er
f
o
r
m
an
ce
an
d
m
itig
ates
o
v
er
f
itti
n
g
,
m
ak
in
g
it
s
u
itab
le
f
o
r
h
a
n
d
lin
g
n
o
is
y
an
d
c
o
m
p
lex
d
ata.
XGBo
o
s
t
co
n
s
tr
u
cts
m
o
d
els
iter
ativ
ely
,
wh
er
e
ea
ch
n
ew
tr
ee
is
d
esig
n
ed
to
a
d
d
r
ess
th
e
m
i
s
tak
es
m
ad
e
b
y
th
e
p
r
ec
ed
in
g
tr
ee
s
,
r
esu
ltin
g
in
i
m
p
r
o
v
e
d
ac
c
u
r
ac
y
.
T
o
f
in
e
-
tu
n
e
th
e
m
o
d
els,
a
5
-
f
o
l
d
cr
o
s
s
-
v
alid
atio
n
m
eth
o
d
was
u
tili
ze
d
with
in
Gr
id
Sear
c
h
C
V,
en
s
u
r
in
g
o
p
tim
al
s
elec
tio
n
o
f
h
y
p
er
p
ar
am
eter
s
.
T
h
e
tr
ain
in
g
s
et
in
clu
d
ed
8
0
0
s
am
p
les,
s
p
lit
in
an
8
0
/2
0
r
atio
,
allo
win
g
b
o
th
m
o
d
els
to
lear
n
r
elatio
n
s
h
ip
s
b
etwe
en
in
p
u
t
s
ig
n
als
(
L
DF,
PP
G,
E
C
G)
an
d
o
u
tp
u
t
lab
el
s
wh
ile
m
ain
tain
in
g
g
en
er
aliza
tio
n
to
u
n
s
ee
n
d
ata.
T
o
im
p
r
o
v
e
class
if
icatio
n
r
eliab
ilit
y
an
d
g
e
n
er
aliza
tio
n
,
p
r
e
d
ictio
n
s
f
r
o
m
b
o
th
tr
ain
e
d
m
o
d
els
wer
e
in
teg
r
ated
th
r
o
u
g
h
an
en
s
em
b
l
e
ap
p
r
o
ac
h
.
4
.
5
.
E
ns
em
ble
s
t
ra
t
eg
y
T
o
en
h
a
n
ce
p
r
e
d
ictiv
e
ac
cu
r
ac
y
an
d
m
o
d
el
s
tab
ilit
y
,
an
en
s
em
b
le
s
tr
ateg
y
was
em
p
lo
y
ed
b
y
co
m
b
in
in
g
p
r
ed
ictio
n
s
g
e
n
er
at
ed
f
r
o
m
b
o
th
r
an
d
o
m
f
o
r
est
an
d
XGBo
o
s
t
m
o
d
els,
wh
ich
we
r
e
o
p
tim
ized
u
s
in
g
Gr
id
Sear
ch
C
V.
T
h
is
s
tr
ateg
y
lev
er
ag
es
th
e
in
d
iv
id
u
al
ad
v
an
tag
es
o
f
f
er
e
d
b
y
ea
c
h
alg
o
r
ith
m
,
r
e
d
u
cin
g
o
v
er
f
itti
n
g
an
d
im
p
r
o
v
in
g
g
en
er
aliza
tio
n
to
u
n
s
ee
n
d
ata.
A
s
o
f
t
v
o
tin
g
m
ec
h
an
is
m
,
im
p
le
m
en
ted
u
s
in
g
s
cik
it
-
lear
n
’
s
Vo
tin
g
C
lass
if
ier
,
wa
s
u
tili
ze
d
,
wh
er
e
eq
u
al
weig
h
ts
wer
e
as
s
ig
n
ed
to
b
o
th
m
o
d
els
p
r
ed
icted
class
p
r
o
b
a
b
ilit
ies,
an
d
th
e
av
er
a
g
ed
p
r
o
b
a
b
ilit
ies d
eter
m
in
ed
th
e
f
in
al
class
if
icatio
n
.
T
h
is
m
eth
o
d
en
s
u
r
es b
alan
ce
d
co
n
tr
ib
u
tio
n
s
b
ased
o
n
ea
ch
m
o
d
el’
s
co
n
f
id
en
ce
,
lead
in
g
to
r
eliab
le
o
u
tco
m
es.
T
h
e
en
s
em
b
le
m
o
d
el
ac
h
iev
ed
s
u
p
er
io
r
p
er
f
o
r
m
a
n
ce
in
co
n
tr
ast
to
u
s
in
g
eith
er
m
o
d
el
in
d
ep
en
d
en
tly
.
Fo
llo
win
g
en
s
em
b
le
in
teg
r
atio
n
,
th
e
f
in
al
m
o
d
el
was e
v
alu
ate
d
u
s
in
g
co
m
p
r
eh
e
n
s
iv
e
p
er
f
o
r
m
an
c
e
m
etr
ics to
v
alid
ate
its
ef
f
ec
tiv
en
ess
.
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
ictio
n
o
f p
erip
h
era
l a
r
teri
a
l d
is
ea
s
e
th
r
o
u
g
h
n
o
n
-
in
va
s
i
ve
d
ia
g
n
o
s
tic
a
p
p
r
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(
S
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b
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Mu
mma
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e
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)
5787
4
.
6
.
M
o
del
e
v
a
lua
t
i
o
n
T
h
e
ef
f
ec
tiv
e
p
e
r
f
o
r
m
an
ce
o
f
r
an
d
o
m
f
o
r
est
,
XGBo
o
s
t,
an
d
th
eir
en
s
em
b
le
was
ev
alu
at
ed
o
n
an
in
d
ep
en
d
en
t
test
d
ataset
b
ased
o
n
c
o
m
m
o
n
ly
u
s
ed
m
etr
ic
s
lik
e
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
e
ca
ll,
an
d
F1
-
s
co
r
e
.
Acc
u
r
ac
y
m
ea
s
u
r
es
th
e
f
r
eq
u
e
n
cy
o
f
c
o
r
r
ec
t
p
r
e
d
ictio
n
s
,
wh
ile
p
r
ec
is
io
n
a
n
d
r
ec
all
e
x
am
i
n
e
th
e
ca
p
ab
ilit
y
o
f
th
e
m
o
d
el
to
co
r
r
ec
tly
d
etec
t
r
elev
an
t
ca
s
es
wh
ile
r
ed
u
cin
g
t
h
e
ch
a
n
ce
o
f
m
is
s
in
g
th
em
.
F
1
-
s
co
r
e,
d
ef
in
e
d
as
th
e
h
ar
m
o
n
ic
m
ea
n
o
f
p
r
ec
is
i
o
n
an
d
r
ec
all,
p
r
o
v
id
es
a
u
n
if
i
ed
m
etr
ic
ca
p
tu
r
in
g
b
o
th
p
r
ec
i
s
io
n
an
d
s
en
s
itiv
ity
in
class
if
icatio
n
.
Ad
d
itio
n
ally
,
co
n
f
u
s
io
n
m
atr
ices
wer
e
an
aly
ze
d
to
ex
am
in
e
class
if
icatio
n
er
r
o
r
s
in
m
o
r
e
d
etail.
T
h
e
en
s
em
b
le
m
o
d
el
co
n
s
is
ten
tly
s
u
r
p
ass
ed
th
e
p
e
r
f
o
r
m
a
n
ce
o
f
th
e
in
d
iv
id
u
al
m
o
d
els
ac
r
o
s
s
all
m
etr
ics,
h
ig
h
lig
h
ti
n
g
im
p
r
o
v
e
d
r
eliab
ilit
y
a
n
d
r
o
b
u
s
tn
ess
b
y
ca
p
italizin
g
o
n
th
e
c
o
m
b
in
e
d
ad
v
a
n
tag
es
f
r
o
m
th
e
s
tr
en
g
th
s
o
f
b
o
th
r
an
d
o
m
f
o
r
est
an
d
XGBo
o
s
t a
lg
o
r
ith
m
s
.
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
r
esear
ch
ev
alu
ates
th
e
class
if
icat
io
n
p
er
f
o
r
m
a
n
ce
o
f
r
an
d
o
m
f
o
r
est
,
XGBo
o
s
t,
an
d
th
eir
en
s
em
b
le
f
o
r
ass
ess
in
g
PAD
s
ev
er
ity
u
s
in
g
p
r
ep
r
o
ce
s
s
ed
p
h
y
s
io
lo
g
ical
f
ea
tu
r
es,
in
clu
d
in
g
L
DF,
PP
G,
an
d
E
C
G
s
ig
n
als.
T
h
e
d
ataset
co
m
p
r
is
ed
1
,
0
0
0
in
s
tan
ce
s
,
with
8
0
%
allo
ca
ted
f
o
r
tr
ain
in
g
a
n
d
2
0
%
f
o
r
test
in
g
.
Mo
d
el
tu
n
i
n
g
was
co
n
d
u
cte
d
u
s
in
g
Gr
id
Sear
c
h
C
V.
C
lass
i
f
icatio
n
ac
cu
r
ac
y
was
em
p
lo
y
ed
as
th
e
p
r
im
a
r
y
ev
alu
atio
n
m
etr
ic,
c
o
m
p
lem
e
n
ted
b
y
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e
f
o
r
a
d
etailed
p
e
r
f
o
r
m
an
ce
an
aly
s
is
.
As
s
u
m
m
ar
ized
in
T
ab
le
1
,
th
e
en
s
em
b
le
ac
h
iev
ed
th
e
h
ig
h
est cla
s
s
if
icatio
n
ac
cu
r
ac
y
o
f
9
3
%,
s
u
r
p
ass
in
g
r
an
d
o
m
f
o
r
est
(
9
0
%)
a
n
d
XGBo
o
s
t
(
9
1
%)
in
d
is
tin
g
u
is
h
in
g
am
o
n
g
n
on
-
PAD,
m
o
d
er
ate
PAD,
an
d
s
ev
er
e
PAD
ca
teg
o
r
ies.
Fig
u
r
e
2
illu
s
tr
ates
th
ese
p
er
f
o
r
m
a
n
ce
d
i
f
f
er
en
ce
s
th
r
o
u
g
h
co
m
p
a
r
ativ
e
ac
c
u
r
ac
y
v
is
u
aliza
tio
n
.
T
h
e
co
n
f
u
s
io
n
m
atr
i
x
in
Fig
u
r
e
3
f
u
r
th
er
h
ig
h
lig
h
ts
th
e
en
s
em
b
le’
s
ef
f
ec
tiv
en
ess
,
p
ar
ticu
lar
ly
in
id
en
tify
in
g
n
on
-
PAD
an
d
s
ev
e
r
e
PAD
ca
s
es.
Sli
g
h
tly
r
ed
u
ce
d
ac
cu
r
a
c
y
in
m
o
d
er
ate
PAD
class
if
ica
tio
n
m
ay
b
e
d
u
e
to
o
v
er
lap
p
i
n
g
p
h
y
s
io
lo
g
ical
p
a
tter
n
s
with
in
th
is
ca
teg
o
r
y
.
T
h
ese
f
in
d
in
g
s
d
em
o
n
s
tr
ate
th
at
th
e
co
m
b
in
ed
f
r
am
ewo
r
k
e
n
h
an
ce
s
p
r
e
d
ictiv
e
ac
cu
r
ac
y
b
y
lev
er
ag
in
g
r
an
d
o
m
f
o
r
est'
s
ca
p
ab
ilit
y
to
m
an
ag
e
h
ig
h
-
d
im
en
s
io
n
al
f
ea
t
u
r
es
an
d
r
ed
u
cin
g
o
v
er
f
itti
n
g
with
XGBo
o
s
t’
s
ab
ilit
y
to
r
ef
in
e
p
r
e
d
ictio
n
s
th
r
o
u
g
h
g
r
ad
ie
n
t
b
o
o
s
tin
g
.
B
y
c
o
m
b
in
i
n
g
th
es
e
m
o
d
els,
th
e
e
n
s
em
b
le
m
iti
g
ates
in
d
iv
id
u
al
m
o
d
el
wea
k
n
ess
es,
ac
h
iev
in
g
a
r
o
b
u
s
t b
alan
ce
o
f
s
en
s
itiv
ity
a
n
d
s
p
ec
if
icity
cr
itical
f
o
r
clin
i
ca
l a
p
p
licatio
n
s
.
Fig
u
r
e
2
.
C
o
m
p
a
r
is
o
n
o
f
class
if
icatio
n
ac
cu
r
ac
y
o
f
d
if
f
er
en
t m
o
d
els f
o
r
PAD
p
r
ed
ictio
n
Fig
u
r
e
3
.
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[
1
]
E.
H
.
W
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i
s
sl
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l
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.
[
2
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J.
S
.
H
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[
3
]
A
.
N
.
La
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.
O
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[
4
]
Y
.
Z
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a
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g
,
J.
H
u
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n
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P
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[
5
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C.
-
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.
Li
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l
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[
6
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R
.
F
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y.
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7
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M
.
E
l
g
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l
.
,
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Th
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[
8
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T.
I
sh
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a
l
.
,
“
L
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ser
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p
p
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[
9
]
A
.
M
.
F
l
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e
s,
F
.
D
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s,
N
.
J
.
Le
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,
a
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d
E
.
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.
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ss
,
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mes
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[
1
0
]
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.
T.
Jo
l
l
i
f
f
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a
d
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ma,
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1
1
]
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.
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p
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[
1
2
]
J.
A
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,
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.
L
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.
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Evaluation Warning : The document was created with Spire.PDF for Python.