I
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ia
n J
o
urna
l o
f
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lect
rica
l En
g
ineering
a
nd
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pu
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er
Science
Vo
l.
42
,
No
.
3
,
J
u
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e
2
0
2
6
,
p
p
.
875
~
88
3
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42
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88
3
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ro
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c
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ry
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ise
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se
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s
a
m
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a
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lt
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b
u
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ig
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li
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in
g
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e
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d
fo
r
a
c
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e
ss
ib
le,
n
o
n
-
i
n
v
a
siv
e
sc
re
e
n
in
g
to
o
ls.
T
h
is
stu
d
y
a
ims
to
d
e
v
e
lo
p
a
p
o
r
tab
le,
re
a
l
-
ti
m
e
in
tern
e
t
o
f
th
i
n
g
s
(
Io
T
)
-
in
teg
ra
ted
e
lec
tro
n
ic
n
o
se
(e
-
n
o
se
)
sy
s
tem
fo
r
COPD
d
e
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ti
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si
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g
e
x
h
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led
v
o
latil
e
o
r
g
a
n
ic
c
o
m
p
o
u
n
d
s
(VO
Cs).
Bre
a
th
sa
m
p
les
fro
m
4
4
p
a
rti
c
ip
a
n
ts
(
h
e
a
lt
h
y
,
sm
o
k
e
rs,
a
n
d
COPD)
we
re
a
n
a
ly
z
e
d
u
sin
g
a
M
OS
-
b
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se
d
e
-
n
o
se
,
a
n
d
f
o
u
r
m
a
c
h
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n
e
-
lea
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in
g
c
las
sifiers
we
re
e
v
a
lu
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ted
.
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ta
we
re
p
ro
c
e
ss
e
d
th
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g
h
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lo
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d
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se
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ted
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n
a
l
y
sis.
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e
ra
n
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o
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fo
re
st
(R
F
)
m
o
d
e
l
a
c
h
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e
d
t
h
e
h
i
g
h
e
st
p
e
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rm
a
n
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e
(a
c
c
u
ra
c
y
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6
%
)
i
n
d
isti
n
g
u
ish
i
n
g
COPD
-
re
late
d
VO
C
p
a
tt
e
rn
s.
Th
is
a
p
p
r
o
a
c
h
o
v
e
rc
o
m
e
s
li
m
it
a
ti
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s
o
f
e
a
rli
e
r
o
ffli
n
e
Ted
lar
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b
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g
m
e
th
o
d
s
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y
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n
a
b
li
n
g
d
irec
t,
re
a
l
-
ti
m
e
b
re
a
th
a
n
a
ly
sis.
T
h
e
p
r
o
t
o
ty
p
e
d
a
sh
b
o
a
rd
p
ro
v
id
e
s
imm
e
d
iate
v
isu
a
li
z
a
ti
o
n
fo
r
p
o
ten
ti
a
l
re
m
o
te
m
o
n
it
o
r
in
g
.
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y
li
m
it
a
ti
o
n
s
in
c
l
u
d
e
th
e
sm
a
ll
s
a
m
p
le
siz
e
a
n
d
n
o
n
-
sta
n
d
a
rd
iz
e
d
b
re
a
th
sa
m
p
li
n
g
,
w
h
ich
m
a
y
a
ffe
c
t
VO
C
v
a
riab
il
it
y
.
Ov
e
ra
ll
,
th
is
w
o
rk
c
o
n
tri
b
u
tes
a
c
o
st
-
e
ffe
c
ti
v
e
,
p
o
rtab
le,
I
o
T
-
e
n
a
b
led
fra
m
e
wo
rk
d
e
m
o
n
str
a
ti
n
g
th
e
fe
a
sib
il
it
y
o
f
re
a
l
-
ti
m
e
VO
C
a
n
a
ly
sis
fo
r
e
a
rly
COPD
sc
re
e
n
in
g
a
n
d
fu
t
u
re
in
teg
ra
ti
o
n
i
n
t
o
tele
h
e
a
lt
h
a
n
d
c
o
m
m
u
n
it
y
-
b
a
se
d
d
iag
n
o
st
i
c
s.
K
ey
w
o
r
d
s
:
C
OPD
E
lectr
o
n
ic
n
o
s
e
I
n
ter
n
et
o
f
th
in
g
s
Ma
ch
in
e
lear
n
in
g
VOCs
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
:
B
u
d
i Y
an
ti
Dep
ar
tm
en
t o
f
Pu
lm
o
n
o
lo
g
y
a
n
d
R
esp
ir
ato
r
y
Me
d
icin
e
,
Sch
o
o
l o
f
Me
d
icin
e
,
Un
iv
e
r
s
itas
S
y
iah
Ku
ala
B
an
d
a
Ace
h
,
I
n
d
o
n
esia
E
m
ail: b
y
an
tip
u
lm
o
n
o
l
o
g
is
t@
u
s
k
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
C
h
r
o
n
ic
r
esp
ir
ato
r
y
d
is
ea
s
es
r
an
k
am
o
n
g
th
e
lead
in
g
g
lo
b
al
ca
u
s
es
o
f
m
o
r
tality
,
with
ch
r
o
n
i
c
o
b
s
tr
u
ctiv
e
p
u
lm
o
n
ar
y
d
is
ea
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e
(
C
OPD
)
af
f
ec
tin
g
1
0
.
3
%
o
f
th
e
wo
r
ld
wid
e
p
o
p
u
latio
n
an
d
p
r
o
jecte
d
to
r
ea
ch
6
0
0
m
illi
o
n
ca
s
es
b
y
2
0
5
0
[
1
]
,
[
2
]
.
M
o
r
e
th
a
n
9
0
%
o
f
C
OPD
-
r
el
ated
d
ea
th
s
o
cc
u
r
in
l
o
w
-
a
n
d
m
id
d
le
-
in
co
m
e
co
u
n
tr
ies
wh
e
r
e
e
x
p
o
s
u
r
e
to
s
m
o
k
in
g
,
h
o
u
s
eh
o
ld
air
p
o
llu
t
io
n
,
a
n
d
o
cc
u
p
atio
n
al
p
ar
ticu
l
ate
m
atter
r
em
ain
s
s
u
b
s
tan
tial
[
3
]
.
T
h
ese
tr
en
d
s
h
ig
h
lig
h
t
th
e
u
r
g
en
t
n
ee
d
f
o
r
ac
ce
s
s
ib
le
an
d
ea
r
ly
d
iag
n
o
s
tic
to
o
ls
,
as
tim
ely
d
etec
tio
n
s
tr
o
n
g
l
y
in
f
lu
e
n
ce
s
lo
n
g
-
ter
m
o
u
tc
o
m
es
[
4
]
.
Alth
o
u
g
h
s
p
ir
o
m
etr
y
is
th
e
d
ia
g
n
o
s
tic
g
o
ld
s
tan
d
a
r
d
f
o
r
C
OPD,
it is
ef
f
o
r
t
-
d
ep
en
d
en
t,
u
n
co
m
f
o
r
tab
le
f
o
r
m
a
n
y
p
atien
ts
,
an
d
u
n
s
u
i
tab
le
f
o
r
wid
esp
r
ea
d
s
cr
ee
n
i
n
g
,
th
u
s
m
o
tiv
atin
g
ex
p
l
o
r
atio
n
o
f
n
o
n
-
in
v
asiv
e
b
io
m
ar
k
e
r
s
s
u
ch
as
ex
h
aled
b
r
ea
th
an
aly
s
is
[
5
]
,
[
6
]
.
E
x
h
a
led
b
r
ea
th
c
o
n
tain
s
h
u
n
d
r
e
d
s
o
f
v
o
latile
o
r
g
an
ic
co
m
p
o
u
n
d
s
(
VOCs
)
th
at
r
ef
lect
m
etab
o
lic
an
d
in
f
la
m
m
at
o
r
y
p
r
o
ce
s
s
es
an
d
h
av
e
b
ee
n
wid
ely
s
tu
d
ied
f
o
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
42
,
No
.
3
,
J
u
n
e
20
26
:
8
7
5
-
88
3
876
d
iag
n
o
s
in
g
r
esp
ir
ato
r
y
a
n
d
s
y
s
tem
ic
d
is
ea
s
e
s
[
7
]
.
C
o
n
v
en
ti
o
n
al
VOC
an
aly
s
is
to
o
ls
s
u
ch
as
GC
-
MS,
PT
R
-
MS,
an
d
I
MS
p
r
o
v
i
d
e
h
ig
h
an
aly
tical
p
r
ec
is
io
n
b
u
t
r
em
ain
i
m
p
r
ac
tical
f
o
r
r
o
u
tin
e
o
r
p
o
in
t
-
of
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ca
r
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d
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e
to
th
eir
co
s
t
an
d
o
p
er
atio
n
al
co
m
p
lex
ity
[
8
]
,
[
9
]
.
R
ec
en
t
ad
v
an
ce
s
h
av
e
ac
ce
ler
ated
th
e
u
s
e
o
f
elec
tr
o
n
ic
n
o
s
es
(e
-
n
o
s
es)
—
p
o
r
tab
le
s
en
s
o
r
-
ar
r
ay
s
y
s
tem
s
ca
p
ab
le
o
f
ca
p
t
u
r
in
g
b
r
ea
th
-
p
r
in
t
p
atter
n
s
u
s
in
g
m
ac
h
i
n
e
-
lear
n
in
g
alg
o
r
ith
m
s
—
o
f
f
er
in
g
a
co
s
t
-
ef
f
ec
tiv
e
an
d
r
a
p
id
ap
p
r
o
ac
h
to
b
r
ea
th
an
aly
s
is
[
1
0
]
.
Mo
d
er
n
e
-
n
o
s
e
d
ev
elo
p
m
e
n
ts
,
in
clu
d
i
n
g
e
n
h
a
n
ce
d
MO
S
-
s
en
s
o
r
a
r
ch
itectu
r
es
an
d
m
ac
h
in
e
-
lear
n
in
g
in
te
g
r
atio
n
,
h
av
e
b
ee
n
d
em
o
n
s
tr
ated
in
r
ec
en
t
s
tu
d
ies
[
1
1
]
,
[
1
2
]
.
T
h
ei
r
d
iag
n
o
s
tic
u
tili
ty
ca
n
b
e
f
u
r
th
er
am
p
lifie
d
th
r
o
u
g
h
in
ter
n
et
o
f
th
i
ngs
(
I
o
T
)
-
en
a
b
led
r
ea
l
-
tim
e
d
ata
ac
q
u
is
itio
n
[
1
3
]
.
T
h
e
I
o
T
en
ab
les
n
etwo
r
k
s
o
f
in
ter
co
n
n
ec
ted
s
en
s
in
g
d
e
v
ices
th
at
ca
n
tr
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s
m
it
h
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lth
d
ata
in
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ea
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tim
e,
im
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g
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ce
s
s
to
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r
e
an
d
s
u
p
p
o
r
tin
g
r
em
o
te
m
o
n
ito
r
in
g
[
1
4
]
,
[
1
5
]
.
I
n
b
r
ea
t
h
-
an
aly
s
is
s
y
s
tem
s
,
I
o
T
allo
ws
s
en
s
o
r
o
u
tp
u
ts
to
b
e
s
to
r
ed
,
s
y
n
ch
r
o
n
ized
,
an
d
v
is
u
alize
d
in
s
tan
tly
th
r
o
u
g
h
clo
u
d
-
b
ased
p
latf
o
r
m
s
,
en
ab
lin
g
p
r
ac
tical
d
ep
lo
y
m
e
n
t
b
ey
o
n
d
h
o
s
p
ital
s
ettin
g
s
.
W
h
en
co
u
p
led
with
m
ac
h
in
e
lear
n
in
g
(
ML
)
,
I
oT
-
in
teg
r
ated
d
ev
ices
ca
n
au
to
m
atica
lly
in
ter
p
r
et
co
m
p
lex
VOC
s
ig
n
atu
r
es,
th
er
eb
y
en
h
an
cin
g
d
iag
n
o
s
tic
r
eliab
ilit
y
an
d
s
ca
lab
ilit
y
[
1
6
]
.
ML
is
a
b
r
an
ch
o
f
ar
tific
ial
in
tellig
en
ce
(
AI
)
th
at
o
f
f
er
s
d
ata
-
d
r
iv
en
r
eso
u
r
ce
s
to
en
h
an
ce
an
d
s
tr
ea
m
lin
e
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
es
[
1
7
]
.
T
h
e
in
tr
o
d
u
cti
o
n
o
f
ML
b
r
i
n
g
s
p
o
te
n
tial
im
p
r
o
v
e
m
en
ts
in
th
e
p
r
ec
is
io
n
an
d
ef
f
ec
tiv
e
n
ess
o
f
ea
r
ly
C
OPD
d
iag
n
o
s
is
,
o
f
f
er
in
g
in
n
o
v
ativ
e
s
tr
ateg
ies
to
ad
d
r
ess
th
e
ex
is
tin
g
d
if
f
i
cu
lties
in
d
etec
tin
g
C
OPD
at
an
ea
r
ly
s
tag
e.
T
h
er
ef
o
r
e
,
we
ex
am
in
e
th
e
latest
s
tu
d
ies
o
n
th
e
u
s
e
o
f
ML
f
o
r
ea
r
ly
C
OPD
s
cr
ee
n
in
g
,
b
o
th
in
o
u
r
co
u
n
tr
y
an
d
g
lo
b
al
ly
[
1
8
]
.
T
h
e
ML
p
r
o
ce
s
s
in
clu
d
es
v
ar
io
u
s
s
tag
es
s
u
ch
as
g
ath
er
in
g
d
ata,
p
r
ep
r
o
ce
s
s
in
g
it,
en
g
in
ee
r
in
g
f
ea
t
u
r
es,
s
elec
tin
g
ap
p
r
o
p
r
iate
m
o
d
els,
tr
ain
in
g
th
em
,
ev
alu
atin
g
p
e
r
f
o
r
m
an
ce
,
o
p
ti
m
izin
g
r
esu
lts
,
an
d
d
ep
lo
y
in
g
th
e
f
in
al
m
o
d
el
[
1
9
]
.
Pre
v
io
u
s
r
esear
ch
co
n
d
u
cted
b
y
Au
lia
et
a
l.
[
2
0
]
in
d
icate
d
th
at
C
OPD
co
u
ld
b
e
id
en
tifie
d
u
s
in
g
an
elec
tr
o
n
ic
n
o
s
e
in
co
n
ju
n
ctio
n
with
a
g
r
ap
h
c
o
n
v
o
lu
tio
n
al
n
etwo
r
k
(
GC
N)
alg
o
r
ith
m
,
u
tili
zin
g
VOCs
,
alth
o
u
g
h
in
th
is
s
tu
d
y
,
th
e
b
r
ea
th
s
am
p
le
d
ata
s
to
r
ed
in
T
ed
lar
b
ag
s
wer
e
p
r
o
ce
s
s
ed
o
f
f
lin
e,
m
ea
n
in
g
th
a
t
th
e
d
etec
tio
n
r
esu
lts
co
u
ld
n
o
t
b
e
d
is
p
l
ay
ed
in
r
ea
l tim
e.
T
h
er
ef
o
r
e,
th
is
s
tu
d
y
p
r
o
p
o
s
e
s
an
ex
h
aled
b
r
ea
th
-
b
ased
s
y
s
tem
f
o
r
ea
r
ly
d
etec
tio
n
o
f
C
OPD
th
at
in
teg
r
ates
th
e
I
o
T
an
d
ML
.
T
h
is
s
y
s
tem
i
s
d
esig
n
ed
to
b
e
p
o
r
tab
le
an
d
ca
p
ab
le
o
f
r
ea
l
-
tim
e
an
aly
s
is
,
allo
win
g
m
ed
ical
p
er
s
o
n
n
el
to
o
b
tain
ex
a
m
in
atio
n
r
esu
lts
in
s
tan
tly
.
Ad
d
itio
n
ally
,
th
e
s
y
s
tem
s
u
p
p
o
r
ts
r
em
o
te
m
o
n
ito
r
in
g
,
en
a
b
lin
g
u
r
b
a
n
s
p
ec
ialis
ts
to
tr
ac
k
th
e
co
n
d
iti
o
n
s
o
f
p
atien
ts
,
in
clu
d
in
g
t
h
o
s
e
in
r
u
r
al
lo
ca
tio
n
s
.
ML
p
r
o
v
i
d
es
p
o
wer
f
u
l
an
aly
ti
ca
l
ca
p
ab
ilit
ies
f
o
r
ex
tr
ac
tin
g
m
ea
n
in
g
f
u
l
p
att
er
n
s
f
r
o
m
h
ig
h
-
d
im
en
s
io
n
al
VOC
d
ata
an
d
h
as
s
h
o
wn
s
u
b
s
tan
tial
p
r
o
m
is
e
f
o
r
ea
r
ly
C
OPD
d
etec
tio
n
[
1
6
]
,
[
1
7
]
.
Ho
we
v
er
,
m
o
s
t
ex
is
tin
g
ML
-
b
ased
e
-
n
o
s
e
s
tu
d
ies
r
ely
o
n
o
f
f
lin
e
b
r
ea
th
-
b
ag
an
al
y
s
is
,
wh
ich
lim
its
r
ea
l
-
tim
e
ap
p
lic
ab
ilit
y
an
d
clin
ical
s
ca
lab
ilit
y
,
as
s
ee
n
in
th
e
s
tu
d
y
o
f
Au
lia
et
a
l.
[
2
0
]
.
T
o
a
d
d
r
ess
th
ese
g
ap
s
,
r
ec
en
t
b
r
ea
th
o
m
ics
s
tu
d
ies
ac
r
o
s
s
d
is
ea
s
es,
in
clu
d
in
g
l
u
n
g
ca
n
c
er
[
2
1
]
,
[
2
2
]
,
asth
m
a
[
2
3
]
,
d
i
ab
etes
m
ellitu
s
[
2
4
]
,
an
d
o
r
al
ca
n
ce
r
[
2
5
]
,
h
av
e
s
h
o
wn
th
e
f
ea
s
ib
ilit
y
o
f
V
OC
-
b
ased
d
iag
n
o
s
tics
,
u
n
d
e
r
s
co
r
in
g
th
e
p
o
ten
tial
f
o
r
b
r
o
ad
e
r
r
esp
ir
at
o
r
y
ap
p
licatio
n
s
.
I
n
lin
e
with
th
ese
d
ev
elo
p
m
e
n
ts
,
th
e
p
r
ese
n
t
s
tu
d
y
in
tr
o
d
u
ce
s
a
p
o
r
tab
le,
r
ea
l
-
tim
e
I
o
T
-
in
teg
r
ated
e
-
n
o
s
e
s
y
s
tem
f
o
r
e
ar
ly
C
OPD
d
etec
tio
n
,
o
v
er
co
m
in
g
lim
itatio
n
s
o
f
o
f
f
lin
e
a
n
aly
s
is
an
d
en
ab
lin
g
im
m
ed
iate
ML
-
b
ased
class
if
icatio
n
an
d
r
em
o
te
v
is
u
aliza
tio
n
.
T
h
e
n
o
v
elty
o
f
th
is
wo
r
k
lies
in
c
o
m
b
in
i
n
g
r
ea
l
-
tim
e
b
r
ea
th
ac
q
u
is
itio
n
,
d
u
al
-
c
lo
u
d
p
r
o
ce
s
s
in
g
,
an
d
I
o
T
-
en
ab
led
m
o
n
ito
r
in
g
in
to
a
u
n
if
ied
,
d
ep
lo
y
a
b
le
C
OPD
s
cr
ee
n
in
g
p
latf
o
r
m
.
2.
M
AT
E
R
I
AL
S AN
D
M
E
T
H
O
DS
2
.
1
.
Su
bje
ct
s
a
nd
re
s
ea
rc
h desi
g
n
B
r
ea
th
s
am
p
les
wer
e
co
llected
f
r
o
m
4
4
m
ale
p
ar
ticip
an
ts
(
2
0
–
7
0
y
ea
r
s
)
at
Z
ain
o
el
Ab
id
in
Gen
er
al
Ho
s
p
ital,
co
n
s
is
tin
g
o
f
1
8
h
e
alth
y
co
n
tr
o
ls
,
1
3
h
ea
v
y
s
m
o
k
er
s
,
a
n
d
1
3
C
OPD
p
atien
ts
.
E
ac
h
p
ar
ticip
an
t
p
r
o
v
id
e
d
3
–
5
b
r
ea
th
s
am
p
les.
C
OPD
was
d
iag
n
o
s
ed
u
s
in
g
s
p
ir
o
m
etr
y
(
FEV1
/FVC
<
7
0
%),
s
u
p
p
o
r
ted
b
y
C
AT
an
d
PUMA
a
s
s
e
s
s
m
en
ts
.
T
o
im
p
r
o
v
e
m
eth
o
d
o
l
o
g
ical
tr
an
s
p
ar
en
cy
,
a
s
u
b
ject
ch
ar
ac
ter
is
tics
tab
le
a
lo
n
g
with
ex
p
licit
in
cl
u
s
io
n
a
n
d
ex
clu
s
io
n
cr
iter
ia
h
as
b
ee
n
a
d
d
e
d
.
T
h
ese
cr
iter
ia
a
d
d
r
ess
c
o
m
m
o
n
c
o
n
f
o
u
n
d
er
s
in
b
r
ea
th
an
aly
s
is
,
s
u
ch
as
r
ec
en
t
in
f
ec
tio
n
s
,
alco
h
o
l
co
n
s
u
m
p
t
io
n
,
o
r
in
ab
ilit
y
t
o
f
o
llo
w
s
tan
d
ar
d
ized
b
r
ea
th
in
g
p
r
o
ce
d
u
r
es,
co
n
s
is
ten
t w
ith
E
R
S tec
h
n
ical
r
ec
o
m
m
en
d
atio
n
s
[
2
6
]
.
Fig
u
r
e
1
h
as
b
ee
n
ex
p
a
n
d
ed
with
a
co
m
p
r
e
h
en
s
iv
e
m
eth
o
d
o
lo
g
y
f
lo
wch
a
r
t
s
h
o
win
g
s
tep
s
f
r
o
m
b
r
ea
th
s
am
p
lin
g
→
s
en
s
o
r
ac
q
u
is
itio
n
→
p
r
ep
r
o
c
ess
in
g
→
clo
u
d
in
teg
r
atio
n
→
ML
tr
ai
n
in
g
→
ev
al
u
atio
n
.
A
d
etailed
ex
p
lan
atio
n
is
ad
d
ed
to
d
escr
ib
e
air
f
lo
w
d
ir
ec
tio
n
,
d
ata
ca
p
tu
r
e,
an
d
p
r
ep
r
o
ce
s
s
in
g
.
Fo
u
r
ML
alg
o
r
ith
m
s
(
lo
g
is
tic
r
eg
r
ess
io
n
(
LR
)
,
K
-
n
ea
r
est
n
eig
h
b
o
r
s
(
KNN
)
,
r
an
d
o
m
f
o
r
est
(
RF
)
,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM
)
)
wer
e
s
elec
ted
d
u
e
to
th
eir
p
r
o
v
en
ef
f
ec
tiv
e
n
ess
in
b
io
m
ed
ical
a
n
d
e
-
n
o
s
e
an
aly
s
is
[
2
7
]
-
[
2
9
]
.
Per
f
o
r
m
an
ce
m
etr
ics also
in
clu
d
e
9
5
% c
o
n
f
id
e
n
ce
in
ter
v
als
an
d
p
-
v
alu
es to
p
r
o
v
id
e
s
tatis
ti
ca
l sig
n
if
ican
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
n
h
a
n
ce
d
d
etec
tio
n
o
f c
h
r
o
n
i
c
o
b
s
tr
u
ct
ive
p
u
lmo
n
a
r
y
d
is
ea
s
e
via
… (
N
u
r
Hid
a
ya
h
N
a
ima
h
Ha
r
a
h
a
p
)
877
Fig
u
r
e
1
.
T
h
e
s
u
g
g
ested
r
esear
ch
d
iag
r
am
2
.
2
.
E
lect
ro
nic no
s
e
Fig
u
r
e
2
h
as
b
ee
n
clar
if
ie
d
t
o
in
clu
d
e
a
s
tep
-
by
-
s
tep
s
y
s
tem
ex
p
lan
atio
n
,
co
v
er
in
g
air
p
ath
way
,
s
en
s
o
r
h
ea
tin
g
,
d
ata
ca
p
t
u
r
e,
an
d
m
ic
r
o
co
n
tr
o
ller
p
r
o
ce
s
s
in
g
.
MO
S
s
en
s
o
r
s
wer
e
s
elec
ted
d
u
e
to
th
ei
r
s
en
s
itiv
ity
an
d
u
s
e
i
n
m
o
d
er
n
e
-
n
o
s
e
s
y
s
tem
s
[
1
1
]
,
[
3
0
]
,
[
3
1
]
.
Ho
wev
er
,
s
am
p
lin
g
in
th
is
s
tu
d
y
was
n
o
t
f
u
lly
co
n
tr
o
lled
,
an
d
f
ac
to
r
s
s
u
ch
as
b
r
ea
th
-
h
o
ld
,
ex
p
ir
ato
r
y
f
l
o
w
r
ate,
an
d
d
ea
d
-
s
p
ac
e
in
clu
s
io
n
m
ay
alter
VOC
co
m
p
o
s
itio
n
as
s
h
o
wn
in
Fig
u
r
e
s
2
(
a)
an
d
(
b
)
.
T
h
ese
in
f
lu
e
n
ce
s
h
av
e
b
ee
n
d
em
o
n
s
tr
ated
in
b
r
ea
th
o
m
ics
an
d
lu
n
g
ca
n
ce
r
r
esear
ch
[
3
1
]
,
a
n
d
E
R
S
g
u
id
elin
es
r
ec
o
m
m
en
d
co
n
tr
o
llin
g
th
ese
v
ar
iab
les
[
2
6
]
.
T
h
is
lim
itatio
n
h
as b
ee
n
ac
k
n
o
wled
g
e
d
ac
co
r
d
in
g
ly
.
(
a)
(
b
)
Fig
u
r
e
2
.
T
h
e
s
etu
p
o
f
th
e
elec
tr
o
n
ic
n
o
s
e
in
th
e
r
esear
ch
(
a)
s
y
s
tem
co
n
f
ig
u
r
atio
n
an
d
(
b
)
i
m
p
lem
en
tatio
n
2
.
3
.
Da
t
a
pro
ce
s
s
ing
T
h
e
s
tag
es o
f
d
ata
p
r
o
ce
s
s
in
g
in
clu
d
e
th
e
f
o
llo
win
g
:
-
Data
clea
n
in
g
:
in
v
o
lv
e
d
r
em
o
v
al
o
f
m
is
s
in
g
o
r
in
co
n
s
is
ten
t
s
en
s
o
r
v
alu
es,
n
o
is
e
tr
im
m
in
g
,
an
d
o
u
tlier
f
ilter
in
g
.
T
h
ese
s
tep
s
ar
e
c
o
n
s
is
ten
t
with
r
ec
o
m
m
en
d
ed
p
r
e
p
r
o
ce
s
s
in
g
p
r
ac
tices
in
VOC
-
b
ased
d
iag
n
o
s
tic
s
tu
d
ies.
-
L
ab
elin
g
:
c
lar
if
ied
th
at
“L
o
w
,
Me
d
iu
m
,
Hig
h
”
r
e
p
r
esen
t
VOC
in
ten
s
ity
cla
s
s
es,
n
o
t
clin
ical
ca
teg
o
r
ies.
T
h
r
esh
o
ld
in
g
was p
er
f
o
r
m
ed
p
er
-
s
en
s
o
r
u
s
in
g
weig
h
ted
c
o
n
tr
ib
u
tio
n
r
u
l
es
.
-
Data
au
g
m
en
tatio
n
:
au
g
m
en
t
atio
n
in
clu
d
ed
g
au
s
s
ian
n
o
is
e
in
jectio
n
,
r
an
d
o
m
s
ca
lin
g
,
an
d
tem
p
o
r
al
jitt
er
in
g
to
s
im
u
late
b
r
ea
th
v
ar
iab
ilit
y
an
d
r
e
d
u
ce
o
v
er
f
itti
n
g
.
T
h
ese
au
g
m
e
n
tatio
n
m
eth
o
d
s
ar
e
co
m
m
o
n
ly
u
s
ed
in
s
m
all
-
s
am
p
le
b
io
m
e
d
ical
s
en
s
o
r
d
atasets
.
-
L
ab
el
en
co
d
in
g
:
ca
teg
o
r
ical
lab
els
ar
e
tr
an
s
f
o
r
m
ed
in
to
n
u
m
er
ical
v
alu
es
u
s
in
g
lab
el
en
co
d
er
s
,
wh
ic
h
en
s
u
r
es
th
ey
ar
e
co
m
p
atib
le
with
ML
alg
o
r
ith
m
s
.
T
h
is
p
r
o
ce
s
s
s
u
p
p
o
r
ts
b
o
th
t
h
e
m
o
d
elin
g
an
d
th
e
ass
es
s
m
en
t o
f
m
o
d
el
p
er
f
o
r
m
a
n
ce
.
-
Data
s
p
litt
in
g
:
a
s
tr
atif
ied
8
0
/2
0
s
p
lit
was
u
s
ed
to
m
ain
tain
cl
ass
b
alan
ce
.
C
r
o
s
s
-
v
alid
atio
n
was
co
n
s
id
er
ed
b
u
t o
m
itted
d
u
e
to
s
m
all
d
atas
et
s
ize;
th
is
is
ac
k
n
o
wled
g
ed
a
s
a
m
eth
o
d
o
lo
g
ical
lim
itatio
n
.
2
.
4
.
M
a
chine le
a
rning
a
lg
o
ri
t
hm
s
a)
LR
:
a
n
o
te
h
as
b
ee
n
ad
d
e
d
in
d
icatin
g
L
R
is
a
f
o
u
n
d
atio
n
al
class
if
ier
u
s
ed
as
a
b
aselin
e
in
b
io
m
e
d
ical
s
ig
n
al
class
if
icatio
n
[
2
7
]
.
b)
SVM
:
with
R
B
F
k
er
n
el
is
wid
ely
u
s
ed
f
o
r
n
o
n
lin
ea
r
VOC
-
b
ased
d
is
ea
s
e
clas
s
if
icatio
n
an
d
s
h
o
ws
s
tr
o
n
g
p
er
f
o
r
m
an
ce
in
e
-
n
o
s
e
r
esp
ir
at
o
r
y
s
tu
d
ies
[
2
8
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
42
,
No
.
3
,
J
u
n
e
20
26
:
8
7
5
-
88
3
878
c)
RF
:
was
in
clu
d
ed
d
u
e
to
its
r
o
b
u
s
tn
ess
to
n
o
is
e
an
d
n
o
n
lin
ea
r
b
io
lo
g
ical
p
atter
n
s
,
co
m
m
o
n
ly
r
ep
o
r
ted
i
n
b
io
m
ed
ical
an
d
b
io
s
en
s
o
r
ML
ap
p
licatio
n
s
[
2
9
]
.
d)
KNN
:
is
ef
f
ec
tiv
e
f
o
r
p
atte
r
n
r
ec
o
g
n
itio
n
in
s
m
all
-
s
am
p
le
VOC
d
atasets
an
d
wid
e
ly
ap
p
lied
in
b
r
ea
th
o
m
ics
[
2
9
]
.
e)
Ma
tr
ix
ev
alu
atio
n
:
m
et
r
ics
wer
e
s
u
p
p
lem
en
te
d
with
9
5
%
co
n
f
i
d
en
ce
in
ter
v
als
co
m
p
u
ted
v
ia
b
o
o
ts
tr
ap
p
in
g
an
d
p
-
v
al
u
e
co
m
p
ar
is
o
n
s
b
etwe
en
class
if
ie
r
s
(
e.
g
.
,
R
F
v
s
SVM)
u
s
in
g
Mc
Nem
ar
’
s
test
to
ass
es
s
s
tati
s
tical
s
ig
n
if
ican
ce
.
f)
I
o
T
:
a
n
o
te
was
ad
d
ed
ac
k
n
o
wled
g
in
g
t
h
at
th
e
s
y
s
tem
’
s
d
e
p
en
d
en
c
y
o
n
co
n
tin
u
o
u
s
in
ter
n
et
co
n
n
ec
tiv
ity
m
ay
af
f
ec
t r
ea
l
-
tim
e
f
u
n
ctio
n
a
lity
in
lo
w
-
b
an
d
wid
th
clin
ical
en
v
ir
o
n
m
en
ts
.
2
.
7
Web
inte
rf
a
ce
des
ig
n
Dash
b
o
ar
d
d
escr
ip
tio
n
ex
p
a
n
d
ed
to
clar
if
y
d
is
p
lay
lo
g
ic,
d
ata
s
y
n
ch
r
o
n
izatio
n
wo
r
k
f
lo
w,
an
d
p
o
ten
tial
in
teg
r
atio
n
with
clin
ical
in
f
o
r
m
atics
s
tan
d
ar
d
s
(
H
L
7
/FHIR).
T
h
e
d
ash
b
o
a
r
d
d
es
ig
n
co
m
p
r
is
es
th
r
ee
p
r
im
ar
y
s
ec
tio
n
s
:
a
s
en
s
o
r
d
a
ta
v
iew,
a
class
if
icatio
n
r
esu
l
ts
d
is
p
lay
,
an
d
a
g
r
ap
h
ical
v
i
s
u
aliza
tio
n
p
an
el.
Sen
s
o
r
r
ea
d
in
g
s
o
b
tain
e
d
f
r
o
m
th
e
MQ
-
3
,
MQ
-
7
,
MQ
-
1
3
5
,
an
d
MG
-
8
1
1
m
o
d
u
les
ar
e
p
r
esen
ted
b
o
t
h
n
u
m
er
ically
an
d
g
r
a
p
h
ically
to
r
ep
r
esen
t
th
e
c
o
n
ce
n
tr
at
io
n
lev
els
o
f
VO
Cs
.
T
h
e
cl
ass
if
icatio
n
s
ec
tio
n
d
is
p
lay
s
th
e
d
iag
n
o
s
tic
ca
teg
o
r
y
p
r
ed
icted
b
y
th
e
m
o
d
el,
id
en
tify
in
g
w
h
eth
er
a
s
am
p
le
co
r
r
esp
o
n
d
s
to
Hea
lth
y
,
Sm
o
k
er
,
o
r
C
OPD
s
t
atu
s
.
Fig
u
r
e
3
p
r
esen
ts
th
e
p
r
o
to
ty
p
e
o
f
th
e
web
d
ash
b
o
ar
d
,
wh
ich
r
em
ain
s
in
th
e
d
e
v
e
l
o
p
m
e
n
t
s
t
a
g
e
a
n
d
s
e
r
v
e
s
a
s
a
c
o
n
c
e
p
t
u
a
l
m
o
d
e
l
f
o
r
i
n
t
e
g
r
a
t
i
n
g
I
o
T
-
b
a
s
e
d
s
e
n
s
i
n
g
w
i
t
h
ML
v
i
s
u
a
l
i
z
a
t
i
o
n
[
3
2
]
.
Fig
u
r
e
3
.
Pro
t
o
ty
p
e
d
esig
n
o
f
th
e
web
-
b
ased
C
OPD
d
etec
tio
n
d
ash
b
o
a
r
d
3.
E
XP
E
R
I
M
E
N
T
A
L
RE
SUL
T
S
3
.
1
.
Da
t
a
s
et
prepa
ra
t
io
n
T
h
e
d
ataset
c
o
m
p
r
is
ed
n
u
m
er
i
ca
l
VOC
r
ea
d
in
g
s
ca
p
tu
r
ed
b
y
th
e
e
-
n
o
s
e
s
y
s
tem
in
r
ea
l
ti
m
e.
Sen
s
o
r
s
ig
n
als
wer
e
tr
an
s
m
itted
f
r
o
m
th
e
E
SP
3
2
m
o
d
u
le
to
Go
o
g
le
Sp
r
ea
d
s
h
ee
t
th
r
o
u
g
h
Go
o
g
le
C
lo
u
d
s
y
n
ch
r
o
n
izatio
n
,
en
s
u
r
i
n
g
c
o
n
tin
u
o
u
s
an
d
tr
ac
ea
b
le
ac
q
u
is
itio
n
.
T
h
is
r
ea
l
-
tim
e
ap
p
r
o
ac
h
p
r
o
v
id
es
an
ad
v
an
tag
e
o
v
er
ea
r
lier
C
OPD
e
-
n
o
s
e
s
tu
d
ies,
wh
ich
ty
p
i
ca
lly
r
elied
o
n
o
f
f
lin
e
T
ed
lar
-
b
ag
co
llectio
n
an
d
d
elay
ed
an
al
y
s
is
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
n
h
a
n
ce
d
d
etec
tio
n
o
f c
h
r
o
n
i
c
o
b
s
tr
u
ct
ive
p
u
lmo
n
a
r
y
d
is
ea
s
e
via
… (
N
u
r
Hid
a
ya
h
N
a
ima
h
Ha
r
a
h
a
p
)
879
Pre
p
r
o
ce
s
s
in
g
in
clu
d
e
d
d
ata
clea
n
in
g
(
r
e
m
o
v
al
o
f
m
i
s
s
in
g
an
d
in
v
alid
v
alu
es)
,
m
in
–
m
ax
n
o
r
m
aliza
tio
n
,
an
d
lab
elin
g
in
to
v
o
c
in
ten
s
ity
class
es
(
lo
w,
m
ed
iu
m
,
an
d
h
ig
h
)
.
T
o
i
n
cr
ea
s
e
r
o
b
u
s
tn
ess
,
au
g
m
en
tatio
n
tech
n
iq
u
es
s
u
c
h
as
Gau
s
s
ian
n
o
is
e
in
ject
io
n
,
r
an
d
o
m
s
ca
lin
g
,
an
d
tem
p
o
r
al
jitt
er
in
g
wer
e
ap
p
lied
.
T
h
ese
au
g
m
e
n
tatio
n
m
eth
o
d
s
a
r
e
co
m
m
o
n
ly
u
s
e
d
in
s
m
all
-
s
am
p
le
b
i
o
m
ed
ica
l
VOC
r
esear
ch
to
im
p
r
o
v
e
g
en
er
aliza
b
ilit
y
.
T
h
e
d
ataset
was
s
p
lit
u
s
in
g
an
8
0
/2
0
s
tr
atif
ied
tr
ain
–
te
s
t
d
iv
is
io
n
to
p
r
eser
v
e
clas
s
b
alan
ce
.
Ad
d
itio
n
al
b
o
o
ts
tr
ap
p
in
g
(
1
,
0
0
0
iter
atio
n
s
)
was
co
n
d
u
ct
ed
to
c
o
m
p
u
te
co
n
f
id
en
ce
i
n
ter
v
als
f
o
r
m
o
d
el
m
etr
ics,
s
tr
en
g
th
en
in
g
th
e
s
tatis
tical
v
alid
ity
o
f
th
e
r
esu
lt
s
.
T
h
is
p
r
ep
ar
atio
n
en
s
u
r
e
d
r
eliab
le
class
if
icatio
n
o
f
VOC
-
b
ased
p
atter
n
s
d
is
tin
g
u
is
h
in
g
Hea
l
th
y
,
Sm
o
k
er
,
an
d
C
OPD
g
r
o
u
p
s
.
3
.
2
.
O
pti
m
izing
ma
chine le
a
rning
E
x
p
lo
r
ato
r
y
d
ata
a
n
aly
s
is
was
co
n
d
u
cte
d
p
r
io
r
to
m
o
d
el
t
r
ain
in
g
.
As
s
h
o
wn
i
n
Fig
u
r
e
4
,
t
-
SNE
v
is
u
aliza
tio
n
r
ev
ea
led
th
r
ee
well
-
s
ep
ar
ated
clu
s
ter
s
,
in
d
icatin
g
th
at
s
en
s
o
r
-
d
er
iv
ed
VO
C
f
ea
tu
r
es
en
co
d
e
d
is
tin
ct
g
r
o
u
p
-
s
p
ec
if
ic
s
ig
n
at
u
r
es.
Similar
s
ep
ar
ab
ilit
y
h
as
b
ee
n
r
e
p
o
r
ted
in
b
r
ea
th
o
m
ics
r
esear
ch
r
elate
d
to
C
OPD
an
d
lu
n
g
ca
n
ce
r
,
d
em
o
n
s
tr
atin
g
th
at
n
o
n
lin
ea
r
d
im
e
n
s
io
n
ality
r
ed
u
ctio
n
e
f
f
ec
tiv
el
y
ca
p
tu
r
es
d
is
ea
s
e
-
r
elate
d
VOC g
r
ad
ien
ts
[
3
3
]
.
Fig
u
r
e
4
.
t
-
SNE
v
is
u
aliza
tio
n
o
f
VOC d
ata
d
is
tr
ib
u
tio
n
ac
r
o
s
s
th
r
ee
lab
el
class
es
T
ab
le
1
s
h
o
ws
d
escr
ip
tiv
e
s
tatis
tics
o
f
r
aw
s
en
s
o
r
r
esp
o
n
s
e
s
,
d
em
o
n
s
tr
atin
g
s
tab
le
s
en
s
o
r
b
eh
av
io
r
.
T
h
e
d
if
f
e
r
in
g
s
en
s
itiv
ities
—
e.
g
.
,
MG
8
1
1
s
h
o
win
g
th
e
h
ig
h
est
m
ea
n
an
d
MQ
7
th
e
g
r
ea
t
est
v
ar
ian
ce
—
alig
n
with
ex
p
ec
ted
g
as
-
s
elec
tiv
ity
p
atter
n
s
o
f
MO
S
s
en
s
o
r
s
,
s
u
p
p
o
r
tin
g
t
h
eir
s
u
itab
ilit
y
f
o
r
d
i
s
ea
s
e
-
r
elate
d
VOC
d
etec
tio
n
.
T
h
is
is
co
n
s
is
ten
t w
ith
p
r
ev
io
u
s
MO
S
-
b
as
ed
b
r
ea
t
h
-
an
aly
s
is
f
in
d
in
g
s
in
r
esp
ir
at
o
r
y
s
tu
d
ies.
T
ab
le
1
.
Descr
ip
tiv
e
s
tatis
tics
o
f
r
aw
VOC s
en
s
o
r
d
ata
b
ef
o
r
e
p
r
ep
r
o
ce
s
s
in
g
I
n
d
e
x
C
o
u
n
t
M
e
a
n
S
t
d
M
i
n
M
a
x
r
a
w
_
m
q
7
3
0
0
0
1
9
1
.
2
7
1
1
6
4
.
2
2
7
1
0
.
4
2
6
6
3
2
.
9
2
4
r
a
w
_
m
q
3
3
0
0
0
1
1
1
7
.
4
3
7
6
2
.
6
1
6
0
.
9
2
1
6
2
7
5
2
.
9
6
r
a
w
_
m
q
1
3
5
3
0
0
0
1
6
3
.
7
1
9
1
1
2
.
3
0
1
0
.
0
4
3
0
.
1
3
1
r
a
w
_
m
g
8
1
1
3
0
0
0
3
3
5
6
.
3
3
8
3
4
.
1
4
1
1
2
0
0
.
9
5
4
1
0
.
8
1
T
h
e
p
er
f
o
r
m
an
ce
o
f
f
o
u
r
ML
class
if
ier
s
(
R
F,
SVM,
KNN,
an
d
L
R
)
was
ev
alu
ated
u
s
in
g
co
n
f
u
s
io
n
m
atr
ices
an
d
b
o
o
ts
tr
ap
p
e
d
9
5
%
co
n
f
id
en
ce
in
ter
v
als.
RF
p
r
o
d
u
ce
d
th
e
m
o
s
t
b
alan
ce
d
clas
s
if
icatio
n
ac
r
o
s
s
all
class
es,
d
em
o
n
s
tr
atin
g
s
u
p
er
io
r
r
o
b
u
s
tn
ess
to
VO
C
v
ar
iab
ilit
y
—
an
ex
p
ec
ted
ad
v
an
ta
g
e
d
u
e
to
its
en
s
em
b
le
s
tr
u
ctu
r
e,
co
m
m
o
n
ly
r
ep
o
r
ted
in
b
io
m
ed
ical
an
d
e
-
n
o
s
e
ap
p
licatio
n
s
.
As
s
h
o
wn
in
T
ab
le
2
,
RF
ac
h
iev
ed
th
e
h
ig
h
est
ac
cu
r
ac
y
(
0
.
8
6
;
9
5
%
C
I
:
0
.
8
2
–
0
.
9
0
)
,
o
u
tp
er
f
o
r
m
i
n
g
SVM
(
0
.
8
1
)
,
KNN
(
0
.
7
9
)
,
an
d
L
R
(
0
.
6
1
)
.
Mc
Nem
ar
’
s
test
co
n
f
ir
m
ed
t
h
at
R
F
s
ig
n
if
ican
tly
o
u
tp
er
f
o
r
m
ed
SVM
(
p
<
0
.
0
5
)
,
v
alid
atin
g
th
e
r
eliab
ilit
y
o
f
th
e
en
s
em
b
le
m
o
d
el.
T
h
e
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
o
f
R
F
alig
n
s
with
p
r
ev
io
u
s
s
tu
d
ies
d
em
o
n
s
tr
atin
g
its
ef
f
ec
tiv
en
ess
in
MO
S e
-
n
o
s
e
b
io
m
ed
ical
class
if
icatio
n
task
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
42
,
No
.
3
,
J
u
n
e
20
26
:
8
7
5
-
88
3
880
T
ab
le
2
.
Per
f
o
r
m
an
ce
co
m
p
a
r
is
o
n
o
f
ML
alg
o
r
ith
m
s
in
C
OP
D
d
etec
tio
n
M
o
d
e
l
A
c
c
u
r
a
c
y
P
r
e
c
i
s
i
o
n
R
e
c
a
l
l
F1
-
s
c
o
r
e
RF
0
.
8
6
0
.
8
6
0
.
8
6
0
.
8
6
S
V
M
0
.
8
1
0
.
8
2
0
.
8
1
0
.
8
1
K
N
N
0
.
7
9
0
.
7
9
0
.
7
8
0
.
7
9
Lo
g
i
s
t
i
c
r
e
g
r
e
ssi
o
n
0
.
6
1
0
.
6
0
0
.
6
1
0
.
6
0
T
o
g
eth
er
,
v
is
u
aliza
tio
n
,
s
tatis
tical
v
alid
atio
n
,
an
d
alg
o
r
ith
m
o
p
tim
izatio
n
co
n
f
ir
m
th
at
th
e
p
r
o
p
o
s
ed
s
y
s
tem
r
eliab
ly
id
en
tifie
s
C
OPD
-
r
elate
d
VOC
s
ig
n
atu
r
es.
T
h
is
alig
n
s
with
r
ec
en
t
b
r
ea
th
o
m
ics
f
in
d
in
g
s
s
h
o
win
g
th
at
MO
S
-
b
ased
e
-
n
o
s
es
ca
n
d
if
f
er
en
tiate
r
esp
ir
ato
r
y
d
is
ea
s
e
s
tates
wh
en
co
m
b
in
e
d
with
ap
p
r
o
p
r
iate
m
ac
h
in
e
-
l
ea
r
n
i
n
g
m
o
d
els.
T
h
is
s
tu
d
y
d
em
o
n
s
tr
ates
th
at
V
OC
s
en
s
o
r
s
ig
n
als
co
n
tain
m
ea
n
in
g
f
u
l
d
is
ea
s
e
-
r
elate
d
v
ar
iatio
n
s
.
t
-
SNE
an
aly
s
is
h
ig
h
lig
h
ts
d
is
tin
ct
VOC
clu
s
ter
s
co
r
r
esp
o
n
d
in
g
to
d
i
f
f
er
en
t
r
esp
ir
ato
r
y
s
tates,
co
n
s
is
ten
t
wi
th
s
im
ila
r
C
OPD
b
r
ea
th
o
m
ics
s
tu
d
ies.
T
h
e
s
ep
ar
atio
n
o
f
clu
s
ter
s
r
ein
f
o
r
ce
s
th
at
th
e
ex
tr
ac
ted
VOC
f
ea
tu
r
es
ca
p
tu
r
e
clin
ically
r
elev
an
t
r
esp
ir
ato
r
y
d
is
tin
ctio
n
s
.
Prio
r
wo
r
k
[3
3
]
s
im
il
ar
ly
s
h
o
wed
th
at
n
o
n
lin
ea
r
v
is
u
aliza
tio
n
s
s
u
ch
as t
-
SNE
h
elp
d
is
tin
g
u
is
h
C
OPD
p
atien
ts
b
ased
o
n
b
r
ea
th
-
g
as c
o
m
p
o
n
en
ts
.
Sen
s
o
r
o
u
tp
u
ts
ex
h
ib
ited
s
tab
le
an
d
in
ter
p
r
etab
le
b
e
h
a
v
io
r
ac
r
o
s
s
r
ec
o
r
d
in
g
s
.
T
h
e
o
b
s
er
v
e
d
s
en
s
itiv
ity
v
ar
iatio
n
s
r
ef
lect
i
n
tr
in
s
ic
MO
S
s
en
s
o
r
ch
ar
ac
te
r
is
tics
,
an
d
s
im
ilar
s
en
s
o
r
-
s
p
e
cif
ic
r
esp
o
n
s
es
h
a
v
e
b
ee
n
r
e
p
o
r
ted
as
b
en
ef
icial
f
o
r
VOC
-
b
ased
d
is
ea
s
e
class
if
ica
tio
n
.
T
h
ese
f
in
d
in
g
s
c
o
n
f
ir
m
th
at
a
p
o
r
tab
le
I
o
T
-
in
teg
r
ated
e
-
n
o
s
e
co
m
b
in
ed
w
ith
ML
ca
n
s
u
p
p
o
r
t
ea
r
ly
C
OPD
d
etec
tio
n
.
R
F
p
er
f
o
r
m
an
c
e
d
em
o
n
s
tr
ates
th
at
n
o
n
lin
ea
r
VOC
f
ea
tu
r
es
ca
n
b
e
ex
p
lo
ited
ef
f
ec
tiv
ely
f
o
r
d
i
s
ea
s
e
d
is
cr
im
in
atio
n
,
co
n
s
is
te
n
t
with
tr
en
d
s
in
e
-
n
o
s
e
r
esp
ir
ato
r
y
d
iag
n
o
s
tics
.
A
lim
itatio
n
o
f
th
e
s
y
s
te
m
is
its
r
elian
ce
o
n
s
tab
le
in
ter
n
et
c
o
n
n
ec
tiv
ity
f
o
r
r
ea
l
-
tim
e
s
y
n
ch
r
o
n
izatio
n
,
an
d
ad
d
itio
n
al
r
ef
in
em
en
ts
ar
e
n
ee
d
ed
to
im
p
r
o
v
e
s
am
p
lin
g
s
tan
d
a
r
d
iz
atio
n
—
p
ar
ticu
lar
ly
b
r
ea
th
-
h
o
ld
d
u
r
atio
n
,
ex
p
i
r
ato
r
y
f
l
o
w,
an
d
d
ea
d
-
s
p
ac
e
elim
in
atio
n
,
wh
ich
ar
e
k
n
o
wn
to
in
f
lu
en
ce
VOC
r
ea
d
in
g
s
in
b
r
ea
th
an
aly
s
is
s
tu
d
ies
[
2
6
]
,
[3
1
]
.
Fu
tu
r
e
wo
r
k
will
ex
p
an
d
th
e
d
ataset,
en
h
a
n
ce
ca
lib
r
atio
n
,
a
n
d
p
r
o
g
r
ess
to
war
d
clin
ical
v
alid
atio
n
.
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
s
u
cc
ess
f
u
lly
d
ev
el
o
p
ed
a
n
I
o
T
-
in
te
g
r
ated
C
OPD
d
etec
tio
n
p
r
o
to
t
y
p
e
t
h
at
co
m
b
in
es
an
elec
tr
o
n
ic
n
o
s
e
with
m
ac
h
in
e
-
lear
n
in
g
an
al
y
s
is
o
f
ex
h
aled
VOCs
.
B
ey
o
n
d
class
if
icatio
n
ac
cu
r
ac
y
,
th
e
wo
r
k
co
n
tr
ib
u
tes
a
r
ea
l
-
tim
e,
p
o
r
tab
le
b
r
ea
th
-
an
al
y
s
is
f
r
am
ewo
r
k
th
at
ad
d
r
ess
es
th
e
lim
itatio
n
s
o
f
p
r
e
v
io
u
s
o
f
f
lin
e
VOC
-
b
ased
C
OP
D
s
y
s
tem
s
.
T
h
e
RF
alg
o
r
ith
m
y
ield
e
d
an
ac
cu
r
ac
y
o
f
8
6
%,
d
em
o
n
s
tr
atin
g
th
e
f
ea
s
ib
ilit
y
o
f
u
s
in
g
en
s
em
b
le
m
o
d
els to
ca
p
tu
r
e
n
o
n
lin
ea
r
r
esp
ir
ato
r
y
VOC s
ig
n
atu
r
es.
T
h
e
d
u
al
-
clo
u
d
a
r
ch
itectu
r
e
(
Go
o
g
le
Dr
iv
e
f
o
r
ac
q
u
is
itio
n
an
d
AW
S
f
o
r
co
m
p
u
tatio
n
)
f
u
r
th
er
h
i
g
h
lig
h
ts
th
e
s
y
s
tem
’
s
p
o
ten
tial
f
o
r
s
ca
lab
le,
d
ata
-
d
r
iv
en
r
esp
ir
ato
r
y
m
o
n
ito
r
in
g
.
I
n
ad
d
itio
n
,
th
e
p
r
o
to
ty
p
e
we
b
in
ter
f
ac
e
d
em
o
n
s
tr
ates
h
o
w
I
o
T
-
b
ased
VOC
m
o
n
ito
r
in
g
c
an
s
u
p
p
o
r
t
r
em
o
te
an
d
c
o
n
tin
u
o
u
s
r
esp
ir
ato
r
y
ass
ess
m
en
t,
p
r
o
v
id
in
g
a
f
o
u
n
d
atio
n
f
o
r
in
teg
r
atio
n
in
t
o
telem
ed
icin
e
an
d
co
m
m
u
n
ity
-
lev
el
s
cr
ee
n
in
g
w
o
r
k
f
lo
ws.
Ho
wev
er
,
s
ev
er
al
lim
itatio
n
s
m
u
s
t
b
e
ac
k
n
o
wled
g
ed
:
th
e
s
am
p
le
s
ize
was
r
elativ
ely
s
m
all,
b
r
ea
th
s
am
p
lin
g
was
n
o
t
s
tr
ictly
s
tan
d
ar
d
ized
(
e.
g
.
,
b
r
ea
t
h
-
h
o
l
d
,
f
lo
w
r
ate,
d
ea
d
s
p
ac
e)
,
an
d
th
e
s
y
s
tem
d
ep
en
d
s
o
n
s
t
ab
le
n
etwo
r
k
co
n
n
ec
tiv
ity
—
f
a
cto
r
s
k
n
o
wn
to
af
f
ec
t
VOC
an
aly
s
is
co
n
s
is
ten
cy
.
Fu
tu
r
e
wo
r
k
will
ad
d
r
ess
th
ese
lim
itatio
n
s
b
y
ex
p
a
n
d
in
g
th
e
p
ar
ticip
a
n
t
co
h
o
r
t,
s
tan
d
ar
d
izin
g
s
a
m
p
lin
g
p
r
o
ce
d
u
r
es,
im
p
r
o
v
i
n
g
s
en
s
o
r
ca
lib
r
atio
n
,
an
d
en
h
an
cin
g
c
lin
ical
in
ter
o
p
er
a
b
ilit
y
(
e.
g
.
,
co
m
p
atib
ilit
y
with
HL
7
/FHIR)
to
s
u
p
p
o
r
t e
v
e
n
tu
al
in
teg
r
atio
n
in
t
o
r
ea
l m
ed
ical
s
y
s
tem
s
.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
e
au
th
o
r
s
ex
p
r
ess
th
eir
s
in
ce
r
e
g
r
atitu
d
e
to
Un
iv
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r
s
itas
S
y
iah
Ku
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th
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x
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h
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e
s
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ch
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T
h
e
au
th
o
r
s
also
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an
k
th
e
Facu
lty
o
f
E
n
g
i
n
ee
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in
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th
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Me
d
ical
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lty
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l o
f
Me
d
icin
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o
f
Un
iv
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s
itas
Sy
iah
Ku
ala
wh
o
co
n
tr
ib
u
ted
to
th
e
im
p
lem
en
ta
tio
n
o
f
th
is
s
tu
d
y
.
FU
NDING
T
h
is
r
esear
ch
r
ec
eiv
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d
a
r
esear
ch
g
r
an
t
f
r
o
m
B
elm
awa
Kem
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s
ain
tek
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ik
ti,
Min
is
tr
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o
f
Hig
h
e
r
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d
u
ca
tio
n
,
Scien
ce
,
a
n
d
T
ec
h
n
o
lo
g
y
o
f
th
e
R
ep
u
b
lic
o
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I
n
d
o
n
esia.
T
h
e
f
u
n
d
in
g
b
o
d
y
h
ad
n
o
r
o
le
in
th
e
s
tu
d
y
d
esig
n
,
d
ata
co
llectio
n
,
d
ata
a
n
aly
s
is
,
in
ter
p
r
etati
o
n
o
f
r
esu
l
ts
,
m
an
u
s
cr
ip
t
p
r
ep
ar
atio
n
,
o
r
d
ec
is
io
n
to
s
u
b
m
it
th
e
ar
ticle
f
o
r
p
u
b
licatio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
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cr
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RE
F
E
R
E
NC
E
S
[
1]
J.
T
i
a
n
e
t
a
l
.
,
“
Ex
h
a
l
e
d
v
o
l
a
t
i
l
e
o
r
g
a
n
i
c
c
o
mp
o
u
n
d
s
a
s
n
o
v
e
l
b
i
o
m
a
r
k
e
r
s
f
o
r
e
a
r
l
y
d
e
t
e
c
t
i
o
n
o
f
C
O
P
D
,
a
st
h
m
a
,
a
n
d
P
R
I
S
m:
a
c
r
o
ss
-
se
c
t
i
o
n
a
l
s
t
u
d
y
,
”
Re
s
p
i
ra
t
o
ry
Re
sea
r
c
h
,
v
o
l
.
2
6
,
n
o
.
1
,
2
0
2
5
,
d
o
i
:
1
0
.
1
1
8
6
/
s1
2
9
3
1
-
025
-
0
3
2
4
2
-
5.
[
2
]
G
l
o
b
a
l
I
n
i
t
i
a
t
i
v
e
f
o
r
C
h
r
o
n
i
c
O
b
s
t
r
u
c
t
i
v
e
L
u
n
g
D
i
se
a
se
(
G
O
LD
)
,
“
G
l
o
b
a
l
i
n
i
t
i
a
t
i
v
e
f
o
r
c
h
r
o
n
i
c
o
b
st
r
u
c
t
i
v
e
l
u
n
g
d
i
sea
se
,
”
2
0
2
5
.
[
3
]
M
.
R
o
d
r
í
g
u
e
z
-
A
g
u
i
l
a
r
e
t
a
l
.
,
“
I
d
e
n
t
i
f
i
c
a
t
i
o
n
o
f
b
r
e
a
t
h
-
p
r
i
n
t
s
f
o
r
t
h
e
C
O
P
D
d
e
t
e
c
t
i
o
n
a
ss
o
c
i
a
t
e
d
w
i
t
h
sm
o
k
i
n
g
a
n
d
h
o
u
s
e
h
o
l
d
a
i
r
p
o
l
l
u
t
i
o
n
b
y
e
l
e
c
t
r
o
n
i
c
n
o
s
e
,
”
R
e
sp
i
r
a
t
o
r
y
M
e
d
i
c
i
n
e
,
v
o
l
.
1
6
3
,
n
o
.
5
5
0
,
p
p
.
1
–
7
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
me
d
.
2
0
2
0
.
1
0
5
9
0
1
.
[
4
]
B
.
C
e
l
l
i
,
“
S
c
r
e
e
n
i
n
g
f
o
r
C
O
P
D
:
c
h
a
l
l
e
n
g
i
n
g
t
h
e
u
n
i
t
e
d
sa
t
e
s
p
r
e
v
e
n
t
i
v
e
s
e
r
v
i
c
e
s
t
a
s
k
f
o
r
c
e
r
e
c
o
m
m
e
n
d
a
t
i
o
n
,
”
C
h
e
st
,
v
o
l
.
1
6
3
,
n
o
.
3
,
p
p
.
4
8
1
–
4
8
3
,
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
h
e
s
t
.
2
0
2
2
.
0
9
.
0
1
8
.
[
5
]
I
.
P
a
n
t
a
z
o
p
o
u
l
o
s
e
t
a
l
.
,
“
I
n
c
o
r
p
o
r
a
t
i
n
g
b
i
o
m
a
r
k
e
r
s
i
n
C
O
P
D
m
a
n
a
g
e
m
e
n
t
:
t
h
e
r
e
s
e
a
r
c
h
k
e
e
p
s
g
o
i
n
g
,
”
J
o
u
rn
a
l
o
f
Pe
rs
o
n
a
l
i
ze
d
Me
d
i
c
i
n
e
,
v
o
l
.
1
2
,
n
o
.
3
,
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
j
p
m1
2
0
3
0
3
7
9
.
[
6
]
S
.
S
c
a
r
l
a
t
a
,
P
.
F
i
n
a
m
o
r
e
,
M
.
M
e
sz
a
r
o
s,
S
.
D
r
a
g
o
n
i
e
r
i
,
a
n
d
A
.
B
i
k
o
v
,
“
T
h
e
r
o
l
e
o
f
e
l
e
c
t
r
o
n
i
c
n
o
s
e
s
i
n
p
h
e
n
o
t
y
p
i
n
g
p
a
t
i
e
n
t
s
w
i
t
h
c
h
r
o
n
i
c
o
b
st
r
u
c
t
i
v
e
p
u
l
m
o
n
a
r
y
d
i
s
e
a
s
e
,
”
Bi
o
se
n
s
o
rs
,
v
o
l
.
1
0
,
n
o
.
1
1
,
p
p
.
1
–
2
0
,
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
B
I
O
S
1
0
1
1
0
1
7
1
.
[
7
]
T.
I
ssi
t
t
,
L
.
W
i
g
g
i
n
s
,
M
.
V
e
y
se
y
,
S
.
T.
S
w
e
e
n
e
y
,
W
.
J.
B
r
a
c
k
e
n
b
u
r
y
,
a
n
d
K
.
R
e
d
e
k
e
r
,
“
V
o
l
a
t
i
l
e
c
o
m
p
o
u
n
d
s
i
n
h
u
ma
n
b
r
e
a
t
h
:
C
r
i
t
i
c
a
l
r
e
v
i
e
w
a
n
d
met
a
-
a
n
a
l
y
s
i
s,
”
J
o
u
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Evaluation Warning : The document was created with Spire.PDF for Python.