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m
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a
n
d
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ti
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.
Biv
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p
s
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twe
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s.
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e
su
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ra
p
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a
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c
teristics
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d
d
e
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o
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imp
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tal
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terv
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s f
o
r
t
h
is u
r
b
a
n
I
n
d
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p
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p
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latio
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.
K
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w
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d
s
:
Dep
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Patien
t h
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q
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Po
p
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aly
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is
Qu
an
titativ
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esear
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R
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-
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Statis
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T
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An
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Dep
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Scie
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PES U
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C
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p
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1.
I
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D
UCT
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O
N
Dep
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is
a
m
ajo
r
m
e
n
tal
h
ea
lth
d
is
o
r
d
er
th
at
af
f
ec
ts
e
m
o
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n
al
well
-
b
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g
,
c
o
g
n
itiv
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f
u
n
ctio
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,
an
d
d
aily
life
ac
tiv
ities
o
f
m
il
lio
n
s
wo
r
ld
wid
e
[
1
]
.
C
o
m
m
o
n
s
y
m
p
to
m
s
in
clu
d
e
s
ad
n
ess
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,
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atig
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o
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eg
ativ
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im
p
ac
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s
o
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al,
s
o
cial,
an
d
o
cc
u
p
atio
n
al
f
u
n
ctio
n
in
g
[
2
]
.
S
o
c
i
o
e
c
o
n
o
m
i
c
s
t
at
u
s
,
i
n
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d
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g
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m
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d
u
c
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t
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m
p
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t
,
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d
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d
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ti
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a
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i
c
u
l
a
r
l
y
d
e
p
r
e
s
s
i
o
n
[
3
]
.
F
a
c
t
o
r
s
s
u
c
h
as
e
d
u
c
a
t
i
o
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p
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f
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n
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lt
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c
a
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o
p
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b
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em
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c
h
o
l
o
g
i
c
a
l
w
el
l
-
b
e
i
n
g
[
4
]
.
Pre
v
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u
s
s
tu
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ies
h
av
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ep
o
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te
d
th
at
lo
wer
s
o
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ec
o
n
o
m
ic
s
tatu
s
is
s
tr
o
n
g
ly
ass
o
ciate
d
w
ith
h
ig
h
e
r
lev
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o
f
d
ep
r
ess
io
n
[
5
]
.
Ho
wev
er
,
m
o
s
t
in
v
esti
g
atio
n
s
wer
e
co
n
d
u
cte
d
in
W
ester
n
p
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p
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latio
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s
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d
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f
ten
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k
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cu
ltu
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d
r
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al
in
f
lu
en
ce
s
o
n
m
en
tal
h
ea
lth
o
u
tco
m
es
[
6
]
.
C
u
ltu
r
al
p
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s
u
r
es,
o
cc
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p
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n
al
s
tr
ess
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an
d
tr
ad
itio
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s
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cial
r
o
les
m
ay
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ig
n
if
ican
tly
in
f
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io
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p
atter
n
s
in
d
if
f
er
en
t
p
o
p
u
latio
n
s
[
7
]
.
I
n
ad
d
itio
n
,
m
an
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r
lier
s
tu
d
i
es
r
elied
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co
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v
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tio
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al
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tatis
tical
ap
p
r
o
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es,
wh
ich
ar
e
lim
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in
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p
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th
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p
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ip
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s
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c
h
o
lo
g
ical
f
ac
to
r
s
[
8
]
,
[
9
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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Dee
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3203
T
r
ad
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ely
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v
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to
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[
1
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.
Alth
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wid
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s
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in
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[
1
1
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.
I
n
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co
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v
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tatis
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tech
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ata
[
1
2
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,
[
1
3
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.
R
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atasets
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p
r
o
ac
h
es m
ay
o
v
e
r
lo
o
k
[
1
4
]
.
Dee
p
lear
n
in
g
m
o
d
els
ca
n
ef
f
ec
tiv
el
y
p
r
o
ce
s
s
h
ig
h
-
d
im
en
s
io
n
al
an
d
m
u
ltimo
d
al
d
ata,
in
cl
u
d
in
g
t
ex
t
an
d
im
ag
es,
lead
in
g
to
im
p
r
o
v
e
d
m
e
n
tal
h
ea
lth
p
r
ed
i
ctio
n
p
e
r
f
o
r
m
an
ce
.
T
h
er
ef
o
r
e,
th
is
s
tu
d
y
p
r
o
p
o
s
es
a
d
ee
p
tr
an
s
f
er
lear
n
in
g
f
r
am
ewo
r
k
f
o
r
ac
c
u
r
ate
d
ep
r
ess
io
n
s
ev
er
ity
class
if
icatio
n
in
u
r
b
an
p
o
p
u
l
atio
n
s
u
s
in
g
p
atien
t
h
ea
lth
q
u
esti
o
n
n
air
e
-
9
(
PHQ
-
9)
d
ata
[
1
5
]
:
i)
t
o
an
aly
ze
d
ep
r
ess
io
n
p
r
e
v
alen
ce
in
m
et
r
o
p
o
litan
p
o
p
u
latio
n
s
u
s
in
g
PHQ
-
9
d
ata
,
ii)
t
o
i
d
en
tify
d
em
o
g
r
ap
h
ic
f
ac
to
r
s
ass
o
ciate
d
with
d
ep
r
ess
io
n
s
e
v
er
ity
,
iii)
t
o
s
u
p
p
o
r
t
d
ata
-
d
r
i
v
en
m
en
tal
h
ea
lth
in
ter
v
e
n
tio
n
s
an
d
p
u
b
lic
h
ea
lth
p
lan
n
in
g
,
an
d
iv
)
t
o
d
ev
el
o
p
a
d
ee
p
tr
an
s
f
er
lear
n
in
g
-
b
ased
f
r
am
ewo
r
k
f
o
r
au
t
o
m
ated
d
ep
r
ess
io
n
class
if
icatio
n
u
s
in
g
m
u
ltimo
d
a
l f
ea
tu
r
e
an
aly
s
is
.
So
m
e
o
f
t
h
e
r
ec
en
t
s
tu
d
ies
r
elate
d
to
o
u
r
wo
r
k
ar
e
r
ev
ie
wed
as
f
o
llo
ws.
T
h
e
au
th
o
r
s
[
1
6
]
–
[
1
8
]
h
ig
h
lig
h
ted
th
e
in
c
r
ea
s
in
g
p
r
e
v
alen
ce
o
f
d
ep
r
ess
io
n
an
d
co
m
m
o
n
m
en
tal
d
is
o
r
d
er
s
in
I
n
d
ia,
em
p
h
asizin
g
th
e
n
ee
d
f
o
r
ea
r
ly
s
cr
ee
n
in
g
,
m
en
tal
h
ea
lth
awa
r
en
ess
,
an
d
ef
f
e
ctiv
e
clin
ical
ass
e
s
s
m
en
t.
T
h
eir
f
in
d
in
g
s
f
u
r
th
er
d
em
o
n
s
tr
ated
s
ig
n
if
ican
t
ass
o
ciatio
n
s
b
etwe
en
d
ep
r
ess
io
n
an
d
f
ac
to
r
s
s
u
ch
as
m
ed
ical
co
m
o
r
b
id
ities
,
ac
ad
em
ic
s
tr
ess
,
an
x
iety
,
a
g
e,
an
d
s
o
cio
-
d
em
o
g
r
ap
h
ic
co
n
d
itio
n
s
.
Fu
r
th
er
m
o
r
e,
Sh
en
o
y
e
t
a
l.
[
1
9
]
id
e
n
tifie
d
an
elev
ated
s
u
icid
e
r
is
k
a
m
o
n
g
in
d
iv
i
d
u
als
with
c
o
m
m
o
n
m
en
tal
d
is
o
r
d
er
s
a
n
d
ch
r
o
n
ic
illn
ess
es,
u
n
d
er
s
co
r
i
n
g
th
e
im
p
o
r
tan
ce
o
f
tar
g
eted
m
en
tal
h
ea
lth
in
ter
v
en
tio
n
s
an
d
p
r
e
v
en
ti
v
e
ca
r
e
s
tr
ateg
ies.
Srin
iv
asan
et
a
l.
[
2
0
]
r
ep
o
r
ted
r
ed
u
ce
d
d
ep
r
ess
io
n
le
v
els
f
o
ll
o
win
g
co
lla
b
o
r
ativ
e
ca
r
e
i
n
ter
v
en
tio
n
s
,
wh
ile
th
e
au
th
o
r
s
[
2
1
]
–
[
2
3
]
v
alid
ated
t
h
e
r
eliab
ilit
y
an
d
e
f
f
ec
tiv
en
e
s
s
o
f
PHQ
-
9
ac
r
o
s
s
d
if
f
er
en
t
d
em
o
g
r
ap
h
ic
a
n
d
cu
ltu
r
al
p
o
p
u
latio
n
s
.
I
n
ad
d
itio
n
,
th
e
r
esear
ch
er
s
[
2
4
]
–
[
2
6
]
h
ig
h
lig
h
ted
th
e
im
p
ac
t
o
f
m
ed
ical
an
d
s
o
cio
d
em
o
g
r
ap
h
ic
f
ac
to
r
s
o
n
d
e
p
r
ess
io
n
ass
ess
m
en
t
an
d
s
cr
ee
n
i
n
g
.
T
h
e
au
th
o
r
s
[
2
7
]
,
[
2
8
]
f
u
r
th
e
r
d
em
o
n
s
tr
ated
th
e
ap
p
licab
ilit
y
o
f
PHQ
-
9
in
d
iv
er
s
e
p
o
p
u
l
atio
n
s
,
em
p
h
asizin
g
th
e
im
p
o
r
tan
ce
o
f
cu
ltu
r
ally
ad
ap
tiv
e
m
e
n
tal
h
ea
lth
ev
al
u
atio
n
ap
p
r
o
ac
h
es.
Uy
u
la
n
et
a
l.
[
2
9
]
d
ev
el
o
p
ed
a
d
ee
p
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
etwo
r
k
(
C
NN
)
-
b
ased
elec
tr
o
en
ce
p
h
alo
g
r
a
p
h
y
(
EEG
)
f
r
am
ewo
r
k
u
s
in
g
R
esNet
-
5
0
,
Mo
b
ileNet,
an
d
I
n
ce
p
tio
n
-
v
3
m
o
d
els
f
o
r
m
a
jo
r
d
e
p
r
ess
iv
e
d
is
o
r
d
er
d
ete
ctio
n
,
d
em
o
n
s
tr
atin
g
th
e
ef
f
ec
tiv
en
ess
o
f
d
ee
p
lear
n
in
g
in
d
ep
r
ess
io
n
d
iag
n
o
s
is
.
Similar
ly
,
So
f
ia
et
a
l
.
[
3
0
]
ap
p
lied
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es
s
u
ch
as
d
ec
is
io
n
tr
ee
,
k
-
n
ea
r
est
n
eig
h
b
o
r
s
,
a
n
d
n
aiv
e
B
ay
es
to
s
u
r
v
ey
-
b
ased
d
ep
r
ess
io
n
ass
ess
m
en
t,
h
ig
h
lig
h
tin
g
th
e
im
p
o
r
tan
ce
o
f
ea
r
l
y
d
etec
tio
n
an
d
a
u
to
m
ated
m
en
tal
h
ea
lth
ev
alu
atio
n
.
Sid
d
iq
u
a
et
a
l.
[
3
1
]
d
e
v
elo
p
ed
m
ac
h
in
e
lear
n
in
g
-
b
ased
a
p
p
r
o
ac
h
es
f
o
r
d
ep
r
ess
io
n
p
r
ed
ictio
n
am
o
n
g
u
n
iv
e
r
s
ity
s
tu
d
en
ts
u
s
in
g
q
u
esti
o
n
n
air
e
d
ata,
wh
ile
L
i
et
a
l.
[
3
2
]
e
x
am
in
ed
th
e
r
elatio
n
s
h
ip
b
et
wee
n
s
u
b
jectiv
e
well
-
b
ein
g
an
d
d
ep
r
ess
io
n
.
I
n
ad
d
itio
n
,
Kim
[
3
3
]
an
aly
ze
d
t
h
e
ass
o
ciatio
n
b
etwe
en
s
o
cio
ec
o
n
o
m
ic
f
ac
to
r
s
an
d
d
ep
r
ess
io
n
u
s
in
g
PHQ
-
9
d
ata
f
r
o
m
a
lar
g
e
p
o
p
u
latio
n
s
t
u
d
y
,
h
ig
h
lig
h
tin
g
t
h
e
in
f
lu
e
n
ce
o
f
in
co
m
e,
ed
u
ca
tio
n
,
m
ar
ital
s
tatu
s
,
an
d
wo
r
k
-
r
elate
d
f
ac
to
r
s
o
n
m
en
ta
l h
ea
lth
o
u
tco
m
es.
Pre
v
io
u
s
s
tu
d
ies
p
r
im
ar
ily
r
e
lied
o
n
tr
ad
itio
n
al
s
tatis
tical
ap
p
r
o
ac
h
es
o
r
b
asic
m
ac
h
i
n
e
lear
n
in
g
tech
n
iq
u
es
f
o
r
d
e
p
r
ess
io
n
an
aly
s
is
.
L
im
ited
r
esear
ch
h
as
in
teg
r
ated
v
alid
ated
clin
ical
m
ea
s
u
r
es
s
u
ch
as
PHQ
-
9
with
m
u
ltimo
d
al
d
ee
p
tr
an
s
f
er
lear
n
in
g
f
r
am
ewo
r
k
s
th
at
co
m
b
in
e
tex
tu
al
an
d
v
is
u
al
f
ea
tu
r
es
f
o
r
au
to
m
ated
d
e
p
r
ess
io
n
d
etec
ti
o
n
.
I
n
ad
d
itio
n
,
th
e
s
ca
lab
ilit
y
an
d
r
ea
l
-
wo
r
ld
ap
p
licab
ilit
y
o
f
s
u
ch
m
o
d
els
in
u
r
b
an
m
en
tal
h
ea
lth
s
ettin
g
s
r
em
ain
u
n
d
er
ex
p
lo
r
ed
.
E
x
is
tin
g
s
tu
d
ies
also
p
r
o
v
id
e
li
m
ited
atten
tio
n
to
co
n
v
o
l
u
tio
n
al
b
lo
ck
atte
n
tio
n
m
o
d
u
le
(
C
B
AM
)
-
b
ased
p
r
etr
ain
ed
ar
c
h
itectu
r
es
f
o
r
im
p
r
o
v
in
g
class
if
icatio
n
p
er
f
o
r
m
an
ce
.
T
h
er
ef
o
r
e,
th
is
s
tu
d
y
p
r
o
p
o
s
es
m
u
ltimo
d
al
d
ee
p
tr
an
s
f
er
lear
n
in
g
-
b
ased
f
r
am
ewo
r
k
in
teg
r
atin
g
R
esNet
-
5
0
,
b
id
ir
ec
tio
n
al
en
c
o
d
er
r
e
p
r
esen
tatio
n
s
f
r
o
m
tr
a
n
s
f
o
r
m
er
s
(
B
E
R
T
)
-
C
NN,
an
d
C
B
AM
-
en
h
an
ce
d
I
n
ce
p
tio
n
V3
a
r
ch
itectu
r
es
to
i
m
p
r
o
v
e
d
ep
r
ess
io
n
class
if
icatio
n
ac
cu
r
ac
y
an
d
s
u
p
p
o
r
t
s
ca
l
ab
le
u
r
b
an
m
en
tal
h
ea
lth
ass
ess
m
en
t.
T
h
e
in
teg
r
atio
n
o
f
m
u
ltimo
d
al
d
ee
p
t
r
an
s
f
er
lear
n
in
g
with
b
io
-
in
s
p
ir
ed
o
p
tim
izatio
n
estab
lis
h
es
a
clin
ically
in
ter
p
r
etab
le
an
d
s
ca
lab
le
ar
tific
ial
i
n
tellig
en
ce
(
AI
)
-
d
r
iv
e
n
f
r
am
e
wo
r
k
f
o
r
d
ep
r
ess
io
n
ass
es
s
m
en
t a
n
d
h
ea
lth
ca
r
e
d
ec
is
io
n
s
u
p
p
o
r
t.
2.
M
E
T
H
O
D
T
h
is
s
tu
d
y
em
p
lo
y
s
a
q
u
an
tita
tiv
e
r
esear
ch
d
esig
n
th
at
u
tili
ze
s
p
o
p
u
latio
n
-
b
ased
m
et
h
o
d
o
lo
g
ies.
T
h
e
o
b
jectiv
e
was
to
ex
am
in
e
th
e
p
r
ev
alen
ce
an
d
ass
o
ciate
d
f
ac
to
r
s
o
f
d
ep
r
ess
io
n
am
o
n
g
in
d
iv
id
u
als
ag
ed
1
7
to
4
0
in
th
e
city
o
f
B
en
g
alu
r
u
,
Kar
n
atak
a.
T
h
e
s
am
p
le
co
m
p
r
is
ed
9
8
7
r
esp
o
n
d
en
t
s
,
s
elec
ted
th
r
o
u
g
h
s
tr
atif
ied
r
an
d
o
m
s
am
p
lin
g
to
en
s
u
r
e
r
ep
r
esen
tatio
n
ac
r
o
s
s
v
ar
io
u
s
d
em
o
g
r
ap
h
ic
g
r
o
u
p
s
.
Data
wer
e
co
llected
u
s
in
g
t
h
e
PHQ
-
9
,
wh
ich
ev
alu
ates
d
ep
r
ess
iv
e
s
y
m
p
to
m
s
ex
p
er
ien
ce
d
o
v
er
th
e
p
r
ec
ed
in
g
f
o
r
tn
ig
h
t.
T
h
e
PHQ
-
9
co
m
p
r
is
es
a
s
er
ies
o
f
n
i
n
e
in
q
u
ir
ies
r
ated
ac
co
r
d
i
n
g
to
a
co
n
tin
u
u
m
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
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15
,
No
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4
,
Au
g
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s
t 2
0
2
6
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3
2
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3
2
1
7
3204
r
esp
o
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at
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Se
v
er
al
d
ay
s
,
"
"M
o
r
e
th
an
h
al
f
th
e
d
ay
s
,
"
an
d
"Ne
ar
ly
ev
er
y
d
ay
"
[
3
4
]
.
T
h
e
r
esp
o
n
s
es
ar
e
ca
teg
o
r
ized
in
to
f
o
u
r
d
is
tin
ct
lev
els
o
f
d
ep
r
ess
iv
e
s
ev
er
ity
:
n
o
r
m
al
(
0
-
9
)
,
m
ild
(
1
0
-
1
3
)
,
m
o
d
er
ate
(
1
4
-
2
0
)
,
an
d
s
ev
e
r
e
(
2
1
-
2
7
)
[
3
5
]
.
T
h
e
co
llected
d
ata
wer
e
an
al
y
ze
d
u
s
in
g
SP
SS
m
ajo
r
tech
n
iq
u
es.
I
n
a
p
r
ev
io
u
s
ly
p
u
b
li
s
h
ed
SP
SS
s
tu
d
y
,
a
b
iv
ar
iate
an
aly
s
is
was
co
n
d
u
cted
to
in
v
esti
g
ate
th
e
v
ar
ied
ass
o
ciatio
n
s
b
etwe
en
d
em
o
g
r
ap
h
ic
f
ac
to
r
s
an
d
d
ep
r
ess
io
n
r
atin
g
.
T
h
e
d
em
o
g
r
ap
h
ic
f
ac
t
o
r
s
wer
e
g
en
d
er
,
lev
el
o
f
ed
u
ca
tio
n
,
ag
e,
in
co
m
e
a
n
d
m
ar
ital
s
tatu
s
.
C
r
o
s
s
tab
s
,
s
y
m
m
etr
ic
m
ea
s
u
r
es,
an
d
t
o
d
eter
m
i
n
e
wh
eth
er
a
c
o
r
r
elatio
n
ex
i
s
ts
at
s
tat
is
tical
ly
s
ig
n
if
ican
t
lev
els,
ch
i
-
s
q
u
ar
e
test
s
wer
e
em
p
lo
y
ed
.
C
o
v
ar
iate
ef
f
ec
ts
o
n
d
ep
r
ess
io
n
,
o
n
th
e
o
th
er
h
an
d
,
wer
e
ex
am
in
ed
u
s
in
g
m
u
ltip
le
r
e
g
r
ess
io
n
an
d
m
u
ltiv
ar
iate
an
al
y
s
is
to
ass
e
s
s
all
p
r
ed
icto
r
s
w
h
ile
co
r
r
ec
tin
g
f
o
r
co
n
f
o
u
n
d
in
g
v
ar
ia
b
les.
2
.
1
.
M
ent
a
l hea
lt
h a
na
ly
s
is
by
pre
-
t
ra
ined m
o
dels
T
h
is
p
r
o
p
o
s
ed
wo
r
k
p
r
esen
ts
a
n
ew
f
r
am
ewo
r
k
b
ased
o
n
d
ee
p
tr
an
s
f
er
lear
n
in
g
,
wh
ic
h
in
clu
d
es
m
u
ltip
le
p
r
etr
ain
ed
m
o
d
els
o
r
g
an
ized
u
s
in
g
a
p
ar
allel
ar
c
h
itectu
r
e
to
s
u
cc
ess
f
u
lly
r
ec
o
g
n
i
ze
d
ep
r
ess
io
n
.
T
h
e
m
o
d
el
f
ea
tu
r
es
a
d
u
al
-
b
r
an
c
h
R
esNet
-
5
0
b
ac
k
b
o
n
e.
I
n
th
e
f
ir
s
t
b
r
an
ch
,
a
B
E
R
T
-
C
NN
h
y
b
r
id
m
o
d
u
l
e
co
m
b
in
es
co
n
tex
t
u
al
s
em
an
tic
(
tex
tu
al)
an
d
l
o
w
-
lev
el
v
is
u
al
in
f
o
r
m
atio
n
f
ea
tu
r
es.
Ad
v
an
ce
d
co
n
tex
tu
a
l
em
b
ed
d
in
g
tech
n
iq
u
es
wer
e
i
n
co
r
p
o
r
ated
to
im
p
r
o
v
e
s
em
a
n
tic
f
ea
tu
r
e
ex
tr
ac
tio
n
f
r
o
m
PHQ
-
9
r
esp
o
n
s
es.
Fu
tu
r
e
ex
ten
s
io
n
s
m
ay
i
n
teg
r
a
te
tr
an
s
f
o
r
m
er
-
b
ased
m
o
d
els
s
u
ch
as
R
o
B
E
R
T
a
an
d
Dis
til
B
E
R
T
f
o
r
en
h
a
n
ce
d
lin
g
u
is
tic
u
n
d
er
s
tan
d
i
n
g
.
I
n
a
d
d
itio
n
,
f
o
ca
l
lo
s
s
an
d
c
o
s
t
-
s
en
s
itiv
e
lear
n
in
g
s
tr
ateg
ies
ca
n
im
p
r
o
v
e
m
in
o
r
ity
class
d
etec
tio
n
,
p
ar
ticu
lar
l
y
f
o
r
s
ev
er
e
d
e
p
r
ess
io
n
ca
teg
o
r
ies.
I
n
t
h
e
s
ec
o
n
d
b
r
an
ch
o
f
th
e
d
u
al
-
b
r
an
c
h
ar
ch
itectu
r
e,
I
n
ce
p
tio
n
V3
is
co
m
b
in
ed
with
th
e
C
B
AM
t
o
id
en
tify
im
p
o
r
ta
n
t
s
p
atial
an
d
ch
a
n
n
el
-
wis
e
f
ea
tu
r
es.
T
h
e
f
ea
tu
r
es
f
r
o
m
b
o
th
b
r
an
ch
es
ar
e
co
n
ca
ten
ate
d
an
d
p
ass
ed
th
r
o
u
g
h
a
f
u
lly
co
n
n
ec
ted
lay
er
f
o
r
f
in
al
lab
el
class
if
icatio
n
.
T
h
is
m
u
ltimo
d
al
co
m
b
i
n
atio
n
s
u
p
p
o
r
ts
d
ep
r
ess
io
n
s
y
m
p
to
m
an
aly
s
is
an
d
p
r
o
m
o
tes
im
p
r
o
v
ed
ea
r
ly
-
s
ta
g
e
d
e
p
r
ess
io
n
id
en
tific
atio
n
an
d
m
e
n
tal
h
ea
lth
m
o
n
ito
r
in
g
.
Fu
r
th
e
r
m
o
r
e
,
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
u
tili
ze
s
th
e
ad
ap
tiv
e
o
s
p
r
ey
o
p
tim
izati
o
n
al
g
o
r
ith
m
(A
-
OOA)
to
o
p
tim
ize
im
p
o
r
tan
t
h
y
p
er
p
ar
am
eter
s
s
u
c
h
as
e
p
o
c
h
s
,
b
atch
s
ize,
an
d
lea
r
n
in
g
r
a
te,
th
er
eb
y
im
p
r
o
v
in
g
class
if
icatio
n
p
e
r
f
o
r
m
an
ce
an
d
co
n
v
er
g
e
n
ce
s
p
ee
d
.
2
.
1
.
1
.
P
re
pro
ce
s
s
ing
Pre
p
r
o
ce
s
s
in
g
is
th
e
f
ir
s
t
s
tep
in
o
u
r
p
r
o
p
o
s
ed
wo
r
k
,
c
o
n
f
ir
m
in
g
th
at
b
o
th
tex
t
u
al
an
d
v
is
u
al
d
ata
ar
e
clea
n
ed
,
co
n
s
is
ten
t,
an
d
r
ea
d
y
f
o
r
f
ea
tu
r
e
e
x
tr
ac
tio
n
.
I
t
also
en
h
an
ce
s
th
e
q
u
ality
o
f
t
h
e
d
ata
an
d
allo
ws
th
e
m
o
d
el
to
b
etter
class
if
y
d
e
p
r
e
s
s
io
n
in
a
m
o
r
e
co
n
s
is
ten
t
way
.
I
n
th
is
wo
r
k
,
d
ata
clea
n
in
g
,
n
o
r
m
aliza
tio
n
,
an
d
m
is
s
in
g
v
alu
e
im
p
u
tatio
n
ar
e
p
er
f
o
r
m
ed
.
i)
Data
clea
n
in
g
:
d
ata
clea
n
i
n
g
e
lim
in
ates
ir
r
elev
an
t
e
n
tr
ies,
s
e
g
m
en
ted
PHQ
-
9
r
esp
o
n
s
es,
d
u
p
licates,
an
d
n
o
is
y
v
is
u
al
s
am
p
les.
Data
p
r
ep
ar
atio
n
f
o
r
tex
t
d
ata
en
tails
r
em
o
v
in
g
ir
r
elev
an
t
ch
a
r
ac
te
r
s
,
wh
ile
p
o
o
r
s
am
p
les o
r
co
r
r
u
p
t im
ag
e
f
iles
ar
e
s
im
p
ly
ex
clu
d
ed
d
u
r
in
g
d
ata
clea
n
in
g
.
T
h
is
r
estricts th
e
tr
ain
in
g
s
et
to
v
alid
,
m
ea
n
in
g
f
u
l in
p
u
ts
f
o
r
th
e
m
o
d
el.
ii)
No
r
m
aliza
tio
n
:
n
o
r
m
aliza
tio
n
g
u
ar
an
tees
th
e
n
u
m
er
ic
f
ea
t
u
r
es
s
u
ch
as
PHQ
-
9
s
co
r
es
o
r
im
ag
e
-
b
ase
d
v
alu
es
,
ar
e
tr
ea
ted
id
en
tically
in
tr
ai
n
in
g
.
No
r
m
aliza
tio
n
r
e
s
ca
les
th
e
f
ea
tu
r
es
to
a
p
ar
tic
u
lar
r
a
n
g
e
th
at
ar
e
n
o
w
all
in
th
e
r
a
n
g
e
o
f
[
0
,
1
]
.
T
h
is
r
ed
u
ce
s
th
e
e
f
f
ec
t
o
f
h
ig
h
-
r
an
g
e
v
alu
es
an
d
allo
ws
th
e
m
o
d
el
to
lear
n
in
a
m
o
r
e
s
tab
le
en
v
ir
o
n
m
en
t.
No
r
m
aliza
tio
n
,
u
s
in
g
th
e
d
ef
in
itio
n
o
f
n
a
r
r
o
win
g
r
an
g
e
m
in
-
m
ax
n
o
r
m
aliza
tio
n
,
is
d
e
f
in
ed
as
(
1
)
.
=
−
(
)
m
ax
(
)
−
(
)
(
1
)
iii)
Miss
in
g
v
alu
e
im
p
u
tatio
n
:
in
co
m
p
lete
r
ec
o
r
d
s
o
r
m
is
s
in
g
P
HQ
-
9
s
co
r
es
ar
e
co
m
m
o
n
in
s
u
r
v
ey
d
ata.
I
n
th
ese
in
s
tan
ce
s
,
co
u
n
ts
o
f
m
is
s
in
g
v
alu
es a
r
e
n
o
t simp
ly
r
e
co
r
d
ed
,
an
d
th
e
u
n
its
ar
e
n
o
t d
is
ca
r
d
ed
.
T
o
f
ill
in
m
is
s
in
g
v
alu
es
th
at
e
x
is
t,
th
e
s
co
r
es
ar
e
f
illed
with
a
s
tat
is
tical
esti
m
ate
to
m
ain
tain
in
teg
r
ity
in
d
ata
(
u
s
e
o
f
m
ea
n
o
r
m
ed
ian
)
.
T
h
is
m
eth
o
d
e
n
s
u
r
es th
er
e
is
co
n
s
i
s
ten
t in
p
u
t f
o
r
d
ee
p
lea
r
n
in
g
a
r
ch
itectu
r
e.
2
.
1
.
2
.
P
a
ra
llel R
esNet
-
5
0
f
o
r
f
ea
t
ure
ex
t
r
a
ct
io
n
Af
ter
p
r
ep
r
o
ce
s
s
in
g
,
th
e
o
u
t
p
u
t
p
r
o
ce
ed
s
in
p
ar
allel
to
two
d
is
tin
ct
b
u
t
c
o
m
p
lem
en
tar
y
d
ee
p
tr
an
s
f
er
lear
n
in
g
p
ath
wa
y
s
R
esNet
with
B
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R
T
alo
n
g
with
co
n
v
o
lu
tio
n
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n
eu
r
al
n
etwo
r
k
(
R
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,
an
d
a
tten
tio
n
-
b
ased
I
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p
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R
esNet
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n
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o
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f
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b
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f
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tatio
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T
h
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tr
ac
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f
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es
ar
e
th
en
s
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ar
ated
in
to
two
p
ar
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b
r
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c
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s
u
b
m
o
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u
les.
T
h
e
f
ir
s
t
b
r
an
ch
im
p
lem
en
ts
B
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R
T
to
m
o
d
el
co
n
tex
tu
al
an
d
s
eq
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tial
d
ep
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d
en
cies,
an
d
th
e
s
ec
o
n
d
b
r
an
c
h
im
p
lem
en
ts
a
C
NN
p
ip
elin
e
t
o
b
u
ild
laten
t
lo
ca
l
p
atter
n
s
f
o
r
th
e
in
p
u
t
d
ata.
T
h
e
o
u
tp
u
ts
o
f
B
E
R
T
an
d
C
NN
ar
e
f
u
s
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to
cr
ea
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an
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n
c
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s
em
an
tic
r
ep
r
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tatio
n
o
f
th
e
o
r
ig
in
al
in
p
u
t.
B
r
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c
h
two
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in
s
with
Evaluation Warning : The document was created with Spire.PDF for Python.
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8
9
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fer lea
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b
u
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atter
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atter
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u
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th
e
f
ea
tu
r
e
m
a
p
s
b
y
s
elec
tin
g
th
e
m
ax
im
u
m
v
alu
e
p
er
s
lid
in
g
win
d
o
w.
T
h
e
p
o
o
lin
g
o
p
e
r
atio
n
ef
f
ec
tiv
ely
r
etain
s
th
e
m
o
s
t
im
p
o
r
tan
t
f
ea
tu
r
es
,
y
et
r
ed
u
ce
s
co
m
p
u
tatio
n
al
b
u
r
d
en
.
At
th
e
en
d
o
f
th
e
m
o
d
el
ar
ch
itectu
r
e,
th
is
f
u
s
es
th
e
o
u
tp
u
t
f
r
o
m
th
e
B
E
R
T
an
d
C
NN
m
o
d
u
les
th
r
o
u
g
h
a
co
n
ca
ten
atio
n
,
in
d
icatin
g
t
h
at
we
h
av
e
co
m
b
in
ed
s
em
an
tic
f
ea
tu
r
es
f
r
o
m
B
E
R
T
with
s
p
atial
f
ea
tu
r
es
f
r
o
m
th
e
C
NN.
T
h
is
co
m
p
lete
r
ep
r
e
s
en
tatio
n
is
th
en
p
ass
ed
o
n
to
th
e
class
if
icat
io
n
p
ip
elin
e.
Ad
d
in
g
r
esid
u
al
lea
r
n
in
g
,
B
E
R
T
's
s
em
an
tic
u
n
d
e
r
s
tan
d
in
g
,
a
n
d
a
h
ier
a
r
ch
ical
v
is
u
al
f
ea
tu
r
e
m
ap
to
g
eth
er
s
tr
en
g
t
h
en
s
th
e
o
v
er
a
ll f
ea
tu
r
e
ex
tr
ac
tio
n
p
r
o
ce
s
s
to
war
d
s
r
ec
o
g
n
izin
g
d
e
p
r
ess
io
n
lev
els.
Atten
tio
n
-
b
ased
I
n
ce
p
tio
n
R
e
s
Net:
th
e
Atten
tio
n
-
I
n
ce
p
tio
n
R
esNet
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tar
t
s
ex
tr
ac
tin
g
f
ea
tu
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f
r
o
m
in
p
u
t
f
ea
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r
es
th
r
o
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g
h
a
R
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5
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b
ac
k
b
o
n
e,
wh
ich
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o
n
s
is
t
s
o
f
a
7
×7
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n
v
o
lu
tio
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f
o
llo
wed
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y
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m
ax
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p
o
o
lin
g
lay
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a
n
d
a
s
er
ies
o
f
r
esid
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al
co
n
v
o
lu
tio
n
al
b
lo
ck
s
with
r
ep
ea
te
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s
eq
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en
ce
s
o
f
th
r
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co
n
v
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l
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tio
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,
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av
in
g
a
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,
3
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th
en
an
o
th
er
1
×
1
co
n
v
o
lu
t
io
n
lay
er
in
r
o
ws,
s
tack
ed
in
s
ev
er
al
s
tag
es.
Af
ter
g
o
in
g
th
r
o
u
g
h
th
e
4
th
r
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u
al
b
lo
ck
,
th
e
h
ig
h
-
le
v
el
f
ea
tu
r
e
r
ep
r
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tatio
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o
u
tp
u
t
is
p
ass
ed
in
to
a
cu
s
to
m
m
o
d
if
icatio
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o
f
th
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I
n
ce
p
tio
n
m
o
d
u
le
,
th
u
s
,
en
h
an
ci
n
g
f
ea
tu
r
e
ex
tr
ac
tio
n
ac
r
o
s
s
m
u
ltip
le
s
ca
les.
T
h
e
I
n
ce
p
tio
n
m
o
d
u
le
allo
ws
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o
r
m
u
lti
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p
ath
f
ea
t
u
r
e
e
x
tr
a
ctio
n
b
y
p
ass
in
g
th
e
in
p
u
t
th
r
o
u
g
h
m
u
ltip
le
co
n
v
o
l
u
tio
n
al
f
ilter
s
(
1
×1
,
3
×
3
,
5
×
5
)
,
an
d
p
o
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lin
g
wo
u
ld
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e
u
n
d
er
tak
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in
p
ar
allel.
T
h
is
allo
ws
th
e
m
o
d
el
to
ac
q
u
ir
e
b
o
th
lo
ca
l
f
i
n
e
-
g
r
ai
n
e
d
ch
ar
ac
ter
is
tics
o
f
th
e
in
p
u
t
d
ata
an
d
lar
g
er
s
p
atial
co
n
tex
t
at
th
e
s
am
e
tim
e
th
r
o
u
g
h
ea
ch
o
f
th
e
v
ar
io
u
s
p
a
th
s
.
T
h
e
o
u
tp
u
ts
o
f
th
e
n
u
m
er
o
u
s
b
r
an
ch
es
a
r
e
c
o
n
ca
ten
ated
in
th
e
d
e
p
th
d
im
en
s
io
n
to
p
r
o
d
u
ce
a
d
en
s
e
an
d
v
ar
ied
s
et
o
f
f
ea
tu
r
es.
A
d
d
itio
n
ally
,
th
e
i
n
clu
s
io
n
o
f
1
×1
c
o
n
v
o
lu
tio
n
o
p
e
r
atio
n
s
a
s
s
is
ts
with
r
ed
u
cin
g
d
im
en
s
io
n
s
an
d
co
m
p
u
tatio
n
al
lo
ad
wh
ile
m
ain
tain
in
g
s
alien
t
in
f
o
r
m
atio
n
.
As
a
m
o
d
u
lar
ar
ch
itectu
r
e,
I
n
ce
p
tio
n
m
o
d
u
les
en
ab
le
s
ca
les
o
f
d
ep
th
an
d
wid
th
o
f
th
e
r
esid
u
al
p
ar
ts
o
f
R
esNet
,
wh
ile
also
d
ec
r
ea
s
in
g
is
s
u
es
o
f
o
v
er
f
itti
n
g
,
v
a
n
is
h
in
g
g
r
ad
ien
ts
,
an
d
m
e
m
o
r
y
is
s
u
es
th
at
ar
is
e
d
u
e
t
o
a
d
ee
p
ar
ch
itectu
r
e
.
T
h
is
u
ltima
tely
lead
s
to
g
r
ea
ter
d
is
cr
im
in
ativ
e
p
o
wer
an
d
g
r
ea
ter
g
en
er
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tio
n
to
war
d
s
co
m
p
lex
v
is
u
al
p
atter
n
s
,
v
alu
ab
le
in
th
e
co
n
tex
t
o
f
s
u
b
t
le
d
ep
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etec
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i
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class
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eth
o
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in
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ap
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u
lti
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T
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ig
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[
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T
h
e
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2
.
1
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3
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Cla
s
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Af
ter
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tr
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e
o
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tp
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ts
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f
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t
h
th
e
R
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B
C
N
N
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d
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R
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ield
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b
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ws
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o
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m
o
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cu
lar
in
f
o
r
m
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(
f
r
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m
R
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C
NN
)
as
well
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m
u
lti
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s
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le
s
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m
A
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R
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o
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id
es
a
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ar
iety
o
f
co
m
b
i
n
atio
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s
o
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l
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f
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tu
r
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ic
h
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d
m
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r
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iv
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tics
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ile
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co
d
in
g
f
in
e
-
g
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ain
ed
v
i
s
u
al
m
in
u
tiae.
T
h
e
f
u
s
ed
f
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tu
r
e
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en
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u
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lly
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ted
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at
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io
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d
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o
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-
lin
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in
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e
,
e
f
f
ec
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ely
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ap
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th
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ig
h
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d
im
en
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io
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e
r
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s
to
b
e
ap
p
r
o
p
r
iate
f
o
r
f
in
al
p
r
ed
ictio
n
.
Dr
o
p
o
u
t
r
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g
u
lar
iz
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ca
n
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e
ap
p
lied
in
th
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g
a
n
d
m
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tain
s
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lear
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g
th
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al
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t
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t
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p
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li
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s
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tiv
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f
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n
ctio
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m
p
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te
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e
p
r
ed
icted
p
r
o
b
ab
ilit
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is
tr
ib
u
tio
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ac
r
o
s
s
th
e
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ef
in
ed
class
es
o
f
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ep
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io
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lev
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s
o
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tm
ax
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u
n
ctio
n
tr
an
s
f
o
r
m
s
th
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m
o
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el
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tp
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t
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in
to
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ilit
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-
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er
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m
a
x
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m
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r
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icted
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a
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tifie
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T
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if
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ip
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o
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Ada
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m
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m
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m
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s
s
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en
tr
o
p
y
lo
s
s
q
u
an
tifie
s
h
o
w
m
u
ch
th
e
p
r
e
d
icted
p
r
o
b
ab
i
lity
d
if
f
er
s
f
r
o
m
th
e
lab
el
g
iv
en
,
a
n
d
th
u
s
,
s
tr
iv
es to
m
in
im
ize
th
e
e
r
r
o
r
i
n
p
r
e
d
ictio
n
as (
7
)
.
=
−
1
∑
[
×
(
ℎ
(
)
)
+
(
1
−
)
×
(
1
−
ℎ
(
)
)
]
=
1
(
7
)
W
h
er
e
s
tan
d
s
f
o
r
th
e
to
tal
a
m
o
u
n
t
o
f
tr
ain
i
n
g
s
am
p
les
in
th
e
d
ataset.
E
ac
h
t
r
ain
in
g
s
am
p
le
is
ch
ar
ac
ter
ized
b
y
two
co
m
p
o
n
en
ts
:
wh
ich
d
en
o
tes
th
e
tar
g
et
lab
el
co
r
r
esp
o
n
d
in
g
to
th
e
tr
ain
in
g
e
x
am
p
le
m
,
a
n
d
wh
ich
r
ep
r
esen
ts
in
p
u
t f
ea
tu
r
es f
o
r
th
at
ex
am
p
le.
ℎ
is
m
o
d
el
p
r
ed
ictio
n
a
n
d
wh
e
r
e
is
m
o
d
el
p
ar
am
eter
.
I
n
itializatio
n
:
t
h
e
alg
o
r
ith
m
b
eg
in
s
b
y
r
an
d
o
m
ly
in
itializin
g
th
e
p
o
s
itio
n
s
o
f
all
o
s
p
r
ey
s
with
in
a
d
ef
in
ed
s
ea
r
ch
s
p
ac
e.
E
ac
h
o
s
p
r
ey
'
s
p
o
s
itio
n
,
in
th
e
−
ℎ
d
im
en
s
io
n
is
d
eter
m
in
e
d
as
in
(
8
)
.
,
=
+
,
∙
(
−
)
,
=
1
,
2
,
…
,
;
=
1
,
2
,
…
,
(
8
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I
n
itial
p
o
s
itio
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o
f
th
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ℎ
o
s
p
r
ey
(
,
)
in
th
e
ℎ
d
im
en
s
io
n
,
lo
wer
(
)
an
d
u
p
p
er
(
)
b
o
u
n
d
s
o
f
th
e
ℎ
p
r
o
b
lem
v
ar
ia
b
le,
r
esp
ec
tiv
ely
.
,
as
a
r
an
d
o
m
n
u
m
b
er
b
etw
ee
n
[
0
,
1
]
,
is
th
e
p
o
p
u
latio
n
s
ize,
is
th
e
p
r
o
b
lem
'
s
s
o
lu
tio
n
d
im
en
s
io
n
,
an
d
in
d
icate
s
th
e
s
p
ec
if
ic
d
im
en
s
io
n
.
E
ac
h
o
s
p
r
ey
s
er
v
es
as
a
ca
n
d
id
ate
s
o
lu
tio
n
,
an
d
its
q
u
ality
is
ev
alu
ated
b
y
th
e
f
itn
ess
v
alu
e
o
f
th
e
o
b
jectiv
e
f
u
n
ctio
n
,
as d
ef
in
e
d
in
(
9
)
.
=
(
)
,
=
1
,
2
,
…
,
(
9
)
W
h
er
e
f
itn
ess
v
alu
e
(
)
o
f
ℎ
o
s
p
r
ey
,
an
d
th
e
p
o
s
itio
n
o
f
ℎ
o
s
p
r
ey
(
).
i)
Ph
ase
1
:
p
o
s
itio
n
in
g
a
n
d
f
is
h
in
g
.
A
t
t
h
is
s
tag
e,
th
e
o
s
p
r
e
y
f
in
d
s
ta
r
g
ets
(
f
is
h
)
an
d
tr
ies
to
ca
tch
th
em
wh
ich
in
v
o
l
v
es
a
lar
g
e
s
h
if
t
in
p
o
s
itio
n
.
T
h
e
o
s
p
r
ey
ch
o
o
s
es
th
e
b
est
p
er
f
o
r
m
in
g
in
d
i
v
id
u
al,
o
r
th
e
o
v
er
all
b
est in
d
iv
i
d
u
al
in
th
e
p
o
p
u
latio
n
,
as its
tar
g
et
as d
ef
in
ed
in
(
1
0
)
.
=
{
|
∈
{
1
,
2
,
…
,
}
∩
<
}
∪
{
}
,
=
1
,
2
,
…
,
(
1
0
)
L
o
ca
tio
n
o
f
ℎ
o
s
p
r
ey
,
p
o
p
u
latio
n
s
ize
,
an
d
f
itn
ess
v
alu
es
o
f
ℎ
an
d
ℎ
o
s
p
r
ey
s
(
)
.
B
est
o
s
p
r
ey
'
s
p
o
s
itio
n
(
)
.
I
n
th
e
s
ea
r
ch
s
p
ac
e,
o
s
p
r
ey
f
in
d
s
a
f
is
h
at
r
an
d
o
m
an
d
attac
k
s
it.
Po
s
itio
n
u
p
d
ate
wh
e
n
o
s
p
r
ey
ap
p
r
o
ac
h
es f
is
h
is
s
im
u
lated
b
y
(
1
1
)
.
,
1
=
,
+
,
∙
(
,
−
,
∙
,
)
,
=
1
,
2
,
…
,
;
=
1
,
2
,
…
,
(
1
1
)
W
h
er
e
ℎ
o
s
p
r
ey
'
s
n
ew
lo
ca
tio
n
in
s
tag
e
1
(
,
1
)
,
wh
e
r
e
,
1
is
it
s
jth
d
im
en
s
io
n
.
Osp
r
e
y
'
s
in
itial
lo
ca
tio
n
(
)
,
an
d
its
jth
d
im
en
s
i
o
n
is
d
en
o
ted
b
y
(
,
)
.
Fis
h
s
elec
ted
b
y
1
st
o
s
p
r
ey
(
,
)
,
an
d
(
,
)
is
a
r
an
d
o
m
n
u
m
b
e
r
in
[
0
,
1
]
.
,
is
ch
o
s
en
at
r
an
d
o
m
f
r
o
m
th
e
{
1
,
2
}
co
llectio
n
.
Acc
o
r
d
in
g
to
(
1
2
)
,
th
e
u
p
d
ated
p
o
s
itio
n
is
m
o
d
if
ied
i
f
it
is
o
u
ts
id
e
th
e
b
o
u
n
d
ar
y
;
if
it
is
b
elo
w
th
e
lo
wer
b
o
u
n
d
,
it
is
s
et
to
th
e
lo
wer
b
o
u
n
d
; if
it is
ab
o
v
e
th
e
u
p
p
er
b
o
u
n
d
,
it is
s
et
to
th
e
u
p
p
er
b
o
u
n
d
.
,
1
=
{
,
1
,
≤
,
1
≤
,
,
1
<
,
,
1
>
(
1
2
)
Prio
r
p
o
s
itio
n
is
r
ep
lace
d
if
r
e
v
is
ed
p
o
s
itio
n
'
s
f
itn
ess
v
alu
e,
as
r
eso
lu
te
b
y
(
1
1
)
a
n
d
(
12
)
,
is
s
u
p
er
io
r
.
T
h
e
u
p
d
ated
p
o
s
itio
n
o
f
o
s
p
r
ey
is
d
er
iv
ed
f
r
o
m
p
r
o
ce
s
s
,
wh
ich
i
s
in
(
1
3
)
.
1
=
{
1
,
1
<
,
1
≥
(
1
3
)
W
h
er
e
f
itn
ess
v
alu
e
(
1
)
o
f
o
s
p
r
ey
'
s
n
ew
lo
ca
tio
n
f
o
llo
win
g
p
h
ase
1
.
Osp
r
ey
'
s
p
o
s
itio
n
f
o
llo
win
g
p
h
ase
1
is
d
en
o
te
d
b
y
1
.
ii)
Ph
ase
2
:
m
o
v
e
f
is
h
to
p
r
o
p
er
s
p
o
t
.
T
h
is
s
tate
r
ep
r
esen
ts
th
e
o
s
p
r
ey
'
s
b
eh
a
v
io
r
as
it
ca
r
r
ie
s
th
e
p
r
ey
to
a
s
af
e
p
lace
wh
ich
is
eq
u
iv
alen
t
to
lo
ca
l
s
ea
r
ch
an
d
r
ef
in
in
g
alr
ea
d
y
s
u
g
g
ested
ca
n
d
i
d
ate
s
o
lu
tio
n
s
.
T
h
is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
Dee
p
tr
a
n
s
fer lea
r
n
in
g
a
r
ch
itectu
r
e
fo
r
d
ep
r
ess
io
n
d
etec
tio
n
u
s
in
g
P
HQ
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9
a
n
a
lysi
s
in
…
(
U
.
A
n
a
n
th
a
n
a
g
u
)
3209
h
as
an
ess
en
tial
p
ar
t
to
p
lay
in
o
p
tim
is
m
b
ec
au
s
e
it
will
en
s
u
r
e
th
at
ea
ch
o
s
p
r
ey
will
b
e
ex
p
lo
r
in
g
th
e
lo
ca
l
ar
ea
o
f
th
e
ca
n
d
id
ate
s
ea
r
ch
s
p
ac
e,
l
o
o
k
in
g
f
o
r
im
p
r
o
v
em
en
t.
T
h
e
p
o
s
itio
n
s
o
f
e
ac
h
ca
n
d
i
d
ate
s
o
lu
tio
n
will
b
e
ad
ju
s
ted
b
ased
o
n
a
s
m
all
p
er
tu
r
b
atio
n
th
at
d
ep
en
d
s
o
n
th
e
cu
r
r
en
t
iter
atio
n
t,
w
h
ic
h
d
ec
r
ea
s
es its
s
ize
wi
th
an
in
cr
ea
s
e
in
iter
atio
n
s
,
en
co
u
r
ag
in
g
tu
n
in
g
,
as d
ef
in
ed
in
(
1
4
)
.
,
2
=
,
1
+
+
,
∙
(
−
)
,
=
1
,
2
,
…
,
(
1
4
)
I
n
p
h
ase
2
,
−
ℎ
o
s
p
r
ey
'
s
n
ew
lo
ca
tio
n
is
,
2
,
an
d
its
ℎ
d
im
en
s
io
n
is
,
2
.
is
th
e
m
ax
im
u
m
n
o
.
o
f
iter
atio
n
s
,
is
cu
r
r
en
t
iter
atio
n
,
an
d
,
is
a
r
an
d
o
m
n
u
m
b
er
in
[
0
,
1
]
.
T
o
en
s
u
r
e
th
at
s
o
lu
tio
n
s
r
e
m
ai
n
with
in
v
alid
b
o
u
n
d
s
,
as d
e
f
in
e
d
in
(
1
5
)
.
,
2
=
{
,
2
,
≤
,
1
≤
,
,
2
<
,
,
2
>
(
1
5
)
T
h
e
f
in
al
p
o
s
itio
n
o
f
o
s
p
r
ey
a
f
ter
lo
ca
l d
ev
elo
p
m
en
t is selected
b
ased
o
n
f
itn
ess
ev
alu
atio
n
as in
(
1
6
)
.
2
=
{
2
,
2
<
1
1
,
2
≥
1
(
1
6
)
W
h
er
e
2
is
th
e
f
itn
ess
v
alu
e
o
f
t
h
e
p
o
s
itio
n
2
,
an
d
2
is
th
e
p
o
s
itio
n
o
f
th
e
o
s
p
r
ey
a
f
ter
p
h
ase
2
.
T
o
im
p
o
s
e
m
o
r
e
s
tr
en
g
th
o
n
th
e
a
b
ilit
y
o
f
th
e
o
p
tim
izer
to
s
tr
ik
e
th
e
e
x
p
lo
r
atio
n
/ex
p
l
o
itatio
n
b
alan
ce
s
o
f
ar
,
it
im
p
lem
en
ts
a
ch
ain
f
o
r
a
g
in
g
m
ec
h
an
is
m
.
T
h
e
ch
ain
f
o
r
a
g
in
g
m
ec
h
an
is
m
e
n
ab
l
es
o
s
p
r
ey
s
to
p
o
ten
tially
eith
er
f
o
llo
w
th
e
g
l
o
b
al
b
est
o
r
m
im
ic
t
h
e
in
d
iv
i
d
u
al
th
at
is
d
ir
ec
tly
b
ef
o
r
e
th
e
m
in
th
e
ch
ain
.
T
h
e
A
-
OOA
b
y
ad
d
in
g
a
ch
ai
n
f
o
r
a
g
in
g
m
ec
h
an
is
m
as
(
1
7
)
.
(
+
1
)
=
{
(
)
+
⋅
(
be
s
t
(
)
−
(
)
)
+
⋅
(
be
s
t
(
)
−
(
)
)
=
1
(
)
+
⋅
(
−
1
(
)
−
(
)
)
+
⋅
(
be
s
t
(
)
−
(
)
)
=
2
,
…
,
(
1
7
)
W
h
er
e
(
)
is
th
e
p
o
s
itio
n
o
f
th
e
i
th
o
s
p
r
ey
in
d
im
en
s
io
n
d
,
be
s
t
(
)
is
g
lo
b
al
b
est
s
o
lu
tio
n
,
∈
[
0
,
1
]
is
th
e
r
an
d
o
m
v
alu
e.
T
h
e
ad
a
p
tiv
e
co
ef
f
icien
t is ca
lcu
lated
a
s
in
(
1
8
)
.
=
2
⋅
⋅
√
|
l
og
(
)
|
(
1
8
)
B
y
ad
d
in
g
th
e
ch
ain
f
o
r
ag
in
g
m
ec
h
an
is
m
to
th
e
o
s
p
r
ey
o
p
ti
m
izatio
n
alg
o
r
ith
m
f
o
r
ad
ap
ti
v
e
tu
n
in
g
,
th
e
m
o
d
el
is
ab
le
to
ad
ap
tiv
ely
tu
n
e
th
e
p
ar
am
eter
s
class
if
icatio
n
p
ar
am
eter
s
s
u
ch
as
ep
o
ch
,
b
atch
s
ize,
an
d
lear
n
in
g
r
ate.
T
h
is
ap
p
r
o
ac
h
im
p
r
o
v
es
co
n
v
er
g
en
ce
b
ec
au
s
e
th
e
f
ir
s
t
o
s
p
r
ey
will
alwa
y
s
f
o
llo
w
th
e
g
lo
b
al
b
est
s
o
lu
tio
n
.
T
h
e
r
est
o
f
th
e
o
s
p
r
e
y
s
will
b
alan
ce
ex
p
lo
r
atio
n
with
th
e
g
lo
b
al
b
est
s
o
lu
tio
n
wh
ile
d
r
if
tin
g
f
r
o
m
th
e
p
r
ev
i
o
u
s
o
s
p
r
ey
.
T
h
is
will
im
p
r
o
v
e
class
if
icatio
n
ac
cu
r
ac
y
wh
ile
av
o
id
in
g
p
r
em
at
u
r
e
co
n
v
er
g
en
ce
a
n
d
k
ee
p
in
g
th
e
p
o
p
u
latio
n
d
iv
e
r
s
e
wh
ile
o
p
ti
m
izin
g
.
T
h
is
wo
u
ld
en
h
an
ce
t
h
e
ac
cu
r
ac
y
i
n
class
if
y
in
g
d
ep
r
ess
io
n
an
d
r
o
b
u
s
tn
ess
wh
en
an
aly
zin
g
a
n
u
r
b
an
p
o
p
u
latio
n
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Descript
iv
e
s
t
a
t
is
t
ics
T
h
e
s
tu
d
y
s
am
p
le'
s
d
escr
ip
tiv
e
s
tatis
tic
s
,
wh
ich
in
clu
d
e
d
em
o
g
r
ap
h
ic
f
ac
to
r
s
a
n
d
PHQ
-
9
q
u
esti
o
n
n
air
e
r
esu
lts
.
T
h
e
m
ea
n
ag
e
o
f
p
a
r
ticip
an
ts
is
2
.
0
0
,
with
a
s
tan
d
ar
d
d
e
v
iatio
n
(
SD)
o
f
1
.
0
0
7
,
s
h
o
win
g
a
d
is
tin
ct
ag
e
g
r
o
u
p
.
Sex
an
d
m
ar
r
ied
s
tatu
s
h
av
e
m
ea
n
v
alu
es
o
f
1
.
5
0
an
d
1
.
5
2
,
r
esp
ec
tiv
ely
,
with
SDs
o
f
0
.
5
0
0
,
in
d
icatin
g
a
b
a
lan
ce
d
r
ep
r
esen
tatio
n
in
b
o
th
ca
teg
o
r
ies.
T
h
e
ed
u
ca
tio
n
al
le
v
el
h
as
a
m
ea
n
o
f
3
.
7
3
a
n
d
a
n
SD
o
f
1
.
2
8
9
,
i
n
d
icatin
g
v
ar
y
in
g
ed
u
ca
tio
n
a
l
lev
els.
I
n
co
m
e
is
ca
lcu
lated
u
s
in
g
a
m
ea
n
o
f
2
.
0
5
a
n
d
a
n
SD
o
f
0
.
8
0
1
.
T
h
e
m
ea
n
s
co
r
es
f
o
r
th
e
PHQ
-
9
item
s
r
an
g
e
f
r
o
m
2
.
2
3
(
PHQ1
)
to
2
.
4
1
(
PHQ9
)
,
with
SDs
o
f
0
.
7
5
9
to
0
.
8
2
3
.
T
h
ese
s
co
r
es
r
ep
r
esen
t
a
m
o
d
er
ate
lev
el
o
f
d
ep
r
ess
io
n
s
y
m
p
to
m
s
r
ep
o
r
ted
b
y
p
ar
ticip
an
ts
,
with
r
esp
o
n
s
es
v
ar
y
in
g
ac
r
o
s
s
q
u
esti
o
n
s
[
6
]
,
[
2
1
]
,
[
2
2
]
.
T
h
e
co
n
s
tan
t
m
ea
n
s
co
r
es
ac
r
o
s
s
PH
Q
q
u
esti
o
n
s
in
d
icate
th
at
th
e
s
am
p
le'
s
ex
p
er
ien
ce
with
d
ep
r
ess
io
n
s
y
m
p
to
m
s
is
b
r
o
ad
ly
h
o
m
o
g
en
eo
u
s
.
3
.
2
.
M
ultiv
a
ria
t
e
t
ests
T
h
e
m
u
ltiv
ar
iate
test
s
th
at
ev
alu
ate
th
e
in
f
l
u
en
ce
s
o
f
i
n
d
ep
en
d
en
t
v
ar
iab
les
(
I
DV)
o
n
co
m
b
in
e
d
d
ep
en
d
e
n
t
v
a
r
iab
les
(
DV)
.
An
in
ter
ce
p
t
h
as
a
h
i
g
h
ly
s
ig
n
if
ican
t
ef
f
ec
t
ac
r
o
s
s
all
m
u
ltiv
ar
iate
test
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
15
,
No
.
4
,
Au
g
u
s
t 2
0
2
6
:
3
2
0
2
-
3
2
1
7
3210
(
W
ilk
s
'
lam
b
d
a
,
Ho
tellin
g
'
s
tr
ac
e
,
R
o
y
'
s
lar
g
est
r
o
o
t
,
an
d
Pil
lai
'
s
tr
ac
e
)
with
a
p
-
v
alu
e
o
f
0
.
0
0
0
,
s
u
g
g
esti
n
g
th
at
th
e
m
o
d
el
ex
p
lain
s
v
ar
ian
ce
.
Ho
wev
er
,
v
ar
iab
le
"
s
ex
"
h
ad
n
o
s
ig
n
if
ican
t e
f
f
ec
t o
n
th
e
DVs,
with
p
-
v
alu
es
o
f
0
.
9
2
6
ac
r
o
s
s
all
test
s
,
in
d
icatin
g
th
at
g
en
d
e
r
d
o
es
n
o
t
s
ig
n
if
ican
tly
co
n
tr
i
b
u
te
t
o
t
h
e
v
a
r
ian
ce
i
n
th
e
o
u
tco
m
es.
T
h
u
s
,
wh
ile
th
e
m
o
d
el
is
g
en
er
ally
ef
f
ec
tiv
e,
"
s
ex
"
as a
v
ar
iab
le
h
as littl
e
ef
f
ec
t.
3
.
3
.
E
s
t
im
a
t
ed
m
a
r
g
ina
l m
e
a
ns
T
h
e
g
r
an
d
m
ea
n
s
h
o
ws
th
e
av
er
ag
e
s
co
r
es
f
o
r
ea
ch
item
o
n
th
e
PHQ.
T
h
e
m
ea
n
s
co
r
es
r
an
g
e
f
r
o
m
2
.
2
3
2
(
PHQ1
)
to
2
.
4
1
1
(
PHQ
9
)
,
with
s
tan
d
ar
d
er
r
o
r
s
o
f
ar
o
u
n
d
0
.
0
2
5
,
d
em
o
n
s
tr
atin
g
s
im
ilar
m
ea
s
u
r
em
en
t
p
r
ec
is
io
n
ac
r
o
s
s
item
s
.
T
h
e
9
5
%
co
n
f
id
en
ce
in
ter
v
als
ar
e
n
ar
r
o
w,
in
d
icatin
g
th
at
th
e
p
o
p
u
latio
n
m
ea
n
s
m
ay
b
e
r
eliab
ly
esti
m
ated
.
T
h
e
v
er
y
eq
u
al
m
ea
n
s
ac
r
o
s
s
PHQ
ite
m
s
s
u
g
g
est
th
at
p
atien
ts
r
ep
o
r
ted
s
im
ilar
lev
els
o
f
s
y
m
p
to
m
s
ac
r
o
s
s
all
q
u
esti
o
n
n
air
e
item
s
,
in
d
icatin
g
a
c
o
n
s
is
ten
t
ex
p
er
ien
ce
with
d
e
p
r
ess
io
n
s
y
m
p
to
m
s
.
PHQ9
h
ad
th
e
h
ig
h
est
m
ea
n
(
2
.
4
1
1
)
,
wh
ic
h
m
ay
r
ef
lect
a
s
o
m
ewh
at
h
ig
h
er
p
r
ev
ale
n
c
e
o
f
th
e
s
y
m
p
t
o
m
s
in
d
icate
d
b
y
th
at
item
.
T
h
e
n
a
r
r
o
w
co
n
f
id
e
n
ce
in
ter
v
als
f
u
r
t
h
er
co
n
f
ir
m
th
e
r
eliab
ilit
y
an
d
co
n
s
is
ten
cy
o
f
th
e
esti
m
ated
PHQ
-
9
item
s
co
r
es.
T
h
e
m
ea
n
f
o
r
g
e
n
d
er
co
m
p
ar
e
s
th
e
av
er
ag
e
s
co
r
es
o
f
m
ales
an
d
f
em
ales
o
n
th
e
PHQ
'
s
n
in
e
co
m
p
o
n
en
ts
.
T
h
e
m
ea
n
s
co
r
e
d
if
f
er
e
n
ce
s
b
etwe
en
m
ales
an
d
f
em
ales
ar
e
m
o
d
est,
in
d
icatin
g
th
at
b
o
th
g
en
d
er
s
e
x
p
er
ien
ce
eq
u
a
l
lev
els
o
f
d
e
p
r
ess
io
n
s
y
m
p
t
o
m
s
.
Mo
s
t
PHQ
item
s
h
av
e
m
o
d
est
v
ar
ian
ce
s
th
at
f
all
with
in
th
e
s
tan
d
ar
d
er
r
o
r
r
an
g
e,
in
d
icatin
g
th
at
th
er
e
is
n
o
s
ig
n
if
ican
t
g
en
d
er
v
a
r
iatio
n
.
Ma
les
h
ad
s
ig
n
if
ican
tly
h
ig
h
er
m
ea
n
s
co
r
es
o
n
PHQs
1
,
4
,
5
,
6
,
a
n
d
8
,
wh
er
ea
s
f
em
ales
h
a
d
s
lig
h
tly
h
ig
h
e
r
m
ea
n
s
o
n
PHQs
2
,
3
,
7
,
an
d
9
.
Ho
wev
er
,
th
ese
d
if
f
er
en
ce
s
a
r
e
m
o
d
est,
an
d
th
e
o
v
e
r
lap
p
in
g
9
5
%
co
n
f
i
d
en
ce
r
an
g
es
in
d
icate
th
at
th
ey
a
r
e
s
tatis
tica
lly
in
s
ig
n
if
ican
t.
3
.
4
.
B
iv
a
ria
t
e
a
na
ly
s
is
3
.
4
.
1
.
Cro
s
s
t
a
b
T
h
e
c
r
o
s
s
t
a
b
u
l
at
i
o
n
o
f
a
g
e
d
i
s
t
r
i
b
u
t
i
o
n
o
f
t
h
e
a
n
s
w
e
r
s
t
o
t
h
e
P
H
Q
i
t
e
m
s
i
n
f
o
u
r
a
g
e
g
r
o
u
p
s
:
1
7
–
2
5
,
26
–
4
0
,
4
0
–
5
0
,
a
n
d
5
0
+
.
P
H
Q
i
t
e
m
s
a
r
e
c
a
t
e
g
o
r
i
z
e
d
i
n
t
o
t
h
r
e
e
r
e
s
p
o
n
s
e
c
a
t
e
g
o
r
i
es
:
"
N
e
a
r
l
y
e
v
e
r
y
d
a
y
,
"
"
S
e
v
e
r
a
l
d
a
y
s
,
"
a
n
d
"
M
o
r
e
t
h
a
n
h
a
l
f
t
h
e
d
a
y
s
,
"
w
h
i
c
h
r
e
p
r
e
s
e
n
t
t
h
e
f
r
e
q
u
e
n
c
y
o
f
s
y
m
p
t
o
m
s
,
r
e
s
p
e
c
ti
v
e
l
y
.
P
HQ
1
r
e
s
u
l
t
s
s
u
g
g
e
s
t
t
h
at
m
o
s
t
p
a
r
t
i
c
i
p
a
n
t
s
in
a
l
l
a
g
e
g
r
o
u
p
s
r
e
p
o
r
t
f
e
e
l
i
n
g
s
y
m
p
t
o
m
s
"
Ne
a
r
l
y
e
v
e
r
y
d
a
y
,
"
w
i
t
h
t
h
e
1
7
–
2
5
a
g
e
g
r
o
u
p
r
e
p
o
r
t
i
n
g
t
h
e
h
i
g
h
e
s
t
f
r
e
q
u
e
n
c
y
(
1
8
.
7
%
)
.
O
t
h
e
r
P
H
Q
ite
m
s
a
ls
o
s
h
o
w
a
s
i
m
il
a
r
p
a
t
t
e
r
n
,
w
i
t
h
y
o
u
n
g
e
r
a
g
e
g
r
o
u
p
s
(
1
7
–
2
5
a
n
d
2
6
–
4
0
)
t
y
p
i
c
a
l
l
y
r
e
p
o
r
t
i
n
g
a
h
i
g
h
e
r
f
r
eq
u
e
n
c
y
o
f
d
e
p
r
e
s
s
i
o
n
s
y
m
p
t
o
m
s
.
I
n
PH
Q
2
,
f
o
r
i
n
s
t
a
n
c
e
,
t
h
e
l
a
r
g
e
s
t
p
e
r
c
e
n
t
a
g
e
o
f
r
e
s
p
o
n
d
e
n
ts
2
1
.
1
%
a
r
e
i
n
t
h
e
1
7
–
2
5
a
g
e
r
a
n
g
e
a
n
d
r
e
p
o
r
t
f
e
e
li
n
g
s
y
m
p
t
o
m
s
"
N
e
a
r
l
y
e
v
e
r
y
d
a
y
"
.
T
h
e
f
r
e
q
u
e
n
c
y
o
f
r
e
p
o
r
t
e
d
s
y
m
p
t
o
m
s
s
e
e
m
s
t
o
d
e
c
l
i
n
e
wi
t
h
a
g
e
.
W
it
h
p
e
r
c
e
n
t
a
g
e
s
r
a
n
g
i
n
g
f
r
o
m
5
.
1
%
(
P
H
Q
1
)
t
o
7
.
3
%
(
PH
Q
8
)
,
t
h
e
5
0
+
a
g
e
g
r
o
u
p
,
f
o
r
e
x
a
m
p
l
e
,
c
o
n
s
is
t
e
n
tl
y
r
e
p
o
r
t
s
lo
w
e
r
p
e
r
c
e
n
t
a
g
e
s
o
f
f
e
e
l
i
n
g
s
y
m
p
t
o
m
s
"
N
e
a
r
l
y
e
v
er
y
d
a
y
"
a
c
r
o
s
s
al
l
PH
Q
i
t
e
m
s
.
T
h
e
h
i
g
h
e
r
p
e
r
c
e
n
t
a
g
e
s
i
n
t
h
e
"
N
e
a
r
l
y
e
v
e
r
y
d
a
y
"
c
a
t
e
g
o
r
y
a
c
r
o
s
s
m
o
s
t
PH
Q
i
t
em
s
i
n
d
i
c
at
e
t
h
at
y
o
u
n
g
e
r
a
g
e
g
r
o
u
p
s
,
e
s
p
e
c
i
al
l
y
t
h
o
s
e
a
g
e
d
1
7
t
o
2
5
,
a
r
e
m
o
r
e
l
i
k
e
l
y
t
o
e
x
p
e
r
i
e
n
c
e
d
e
p
r
ess
e
d
s
y
m
p
t
o
m
s
m
o
r
e
f
r
e
q
u
e
n
t
l
y
,
a
cc
o
r
d
i
n
g
t
o
t
h
e
r
e
s
e
a
r
c
h
[
5
]
,
[
1
0
]
,
[
3
5
]
.
3
.
4
.
2
.
Chi
-
s
qu
a
re
t
ests
T
h
e
ch
i
-
s
q
u
ar
e
test
s
f
o
r
ag
e
ac
r
o
s
s
th
e
n
in
e
PHQ
item
s
to
d
eter
m
in
e
wh
eth
er
th
er
e
ar
e
an
y
s
ig
n
if
ican
t
co
n
n
ec
tio
n
s
b
etwe
en
ag
e
g
r
o
u
p
s
an
d
th
e
f
r
eq
u
e
n
cy
o
f
d
ep
r
ess
ed
s
y
m
p
to
m
s
.
P
HQ1
an
d
PHQ2
h
ad
Pear
s
o
n
ch
i
-
s
q
u
ar
e
v
alu
es
o
f
8
.
5
2
2
a
n
d
8
.
3
2
2
,
r
esp
ec
tiv
ely
,
with
p
-
v
alu
es
o
f
.
2
0
2
a
n
d
.
2
1
5
.
T
h
ese
f
in
d
i
n
g
s
s
h
o
w
n
o
s
tatis
tically
s
ig
n
if
ican
t
r
elatio
n
s
h
ip
b
etwe
en
ag
e
g
r
o
u
p
s
an
d
r
esp
o
n
s
es
to
t
h
ese
item
s
,
as
th
e
p
-
v
alu
es
ab
o
v
e
th
e
co
n
v
en
tio
n
al
s
ig
n
if
ican
ce
lev
el
o
f
0
.
0
5
.
Pear
s
o
n
ch
i
-
s
q
u
ar
e
v
al
u
es
f
o
r
PHQ3
an
d
PHQ4
a
r
e
1
1
.
9
2
3
an
d
1
1
.
3
6
6
,
with
p
-
v
a
lu
es
o
f
.
0
6
4
an
d
.
0
7
8
,
r
esp
ec
ti
v
ely
.
T
h
ese
f
in
d
in
g
s
in
d
icate
a
ten
d
en
c
y
to
war
d
s
ig
n
if
ican
ce
,
p
a
r
ticu
lar
ly
f
o
r
PHQ3
,
wh
er
e
th
e
p
-
v
alu
e
is
n
ea
r
0
.
0
5
.
Ho
wev
er
,
n
eith
er
ac
h
iev
es
co
n
v
en
tio
n
al
s
tatis
t
ical
s
ig
n
if
ican
ce
.
Pear
s
o
n
ch
i
-
s
q
u
ar
e
v
alu
es
f
o
r
PHQ
s
5
–
9
r
an
g
e
f
r
o
m
1
.
8
2
5
to
6
.
7
2
1
,
with
p
-
v
alu
es
b
etwe
en
0
.
9
3
5
a
n
d
0
.
3
4
7
.
T
h
ese
f
in
d
in
g
s
r
ep
ea
ted
ly
r
ev
ea
l
n
o
s
ig
n
if
ican
t
r
elatio
n
s
h
i
p
b
etwe
en
a
g
e
an
d
d
ep
r
ess
io
n
s
y
m
p
to
m
s
f
o
r
th
ese
m
ea
s
u
r
es,
with
all
p
-
v
alu
es
o
v
er
0
.
0
5
.
Ov
er
all,
th
e
f
in
d
in
g
s
in
d
icate
th
at
a
g
e
h
as
n
o
s
ig
n
if
ican
t
im
p
ac
t
o
n
th
e
f
r
eq
u
en
c
y
o
f
d
ep
r
ess
ed
s
y
m
p
to
m
s
as
ju
d
g
ed
b
y
th
e
PHQ
item
s
in
th
i
s
p
o
p
u
latio
n
.
T
h
e
Pear
s
o
n
ch
i
-
s
q
u
ar
e
v
alu
es
f
o
r
all
n
in
e
PHQ
item
s
(
PHQ1
th
r
o
u
g
h
PHQ9
)
r
an
g
e
f
r
o
m
0
.
1
9
4
to
2
.
1
8
4
,
with
c
o
r
r
esp
o
n
d
in
g
p
-
v
alu
es
o
f
.
3
3
5
to
.
9
0
8
.
T
h
ese
p
-
v
alu
es
a
r
e
s
ig
n
if
ican
tly
ab
o
v
e
t
h
e
s
tan
d
ar
d
s
ig
n
if
ican
ce
lev
el
o
f
0
.
0
5
,
d
e
m
o
n
s
tr
atin
g
th
at
th
er
e
is
n
o
s
tati
s
tically
s
ig
n
if
ican
t
co
r
r
elatio
n
b
etwe
en
r
esp
o
n
s
es to
an
y
o
f
th
e
PHQ
it
em
s
an
d
g
en
d
er
.
3
.
5
.
P
re
t
ra
ined
m
o
del a
na
ly
s
is
T
h
e
p
r
o
p
o
s
ed
d
ep
r
ess
io
n
class
if
icatio
n
f
r
am
ewo
r
k
will
b
e
ev
alu
ated
s
y
s
tem
atica
lly
ag
ai
n
s
t
a
g
r
o
u
p
o
f
p
r
etr
ain
ed
m
o
d
els
u
s
in
g
a
wid
e
r
an
g
e
o
f
p
er
f
o
r
m
an
c
e
m
etr
ics
in
clu
d
in
g
p
r
ec
is
io
n
,
r
ec
all,
ac
cu
r
ac
y
,
F1
-
s
co
r
e,
s
p
ec
if
icity
,
f
alse
p
o
s
itiv
e
r
ate
(
FP
R
)
,
n
eg
ati
v
e
p
r
ed
ictiv
e
v
alu
e
(
NPV)
,
f
alse
n
eg
ativ
e
r
ate
(
FNR
)
,
ar
ea
u
n
d
er
th
e
cu
r
v
e
-
r
ec
eiv
e
r
o
p
er
atin
g
ch
a
r
ac
ter
is
tic
(
AUC
-
R
O
C
),
an
d
Ma
tth
ew’
s
co
r
r
elatio
n
co
ef
f
icien
t
(
MCC
)
.
T
h
e
m
o
d
els
will
b
e
ev
alu
ated
b
ased
o
n
ea
ch
m
o
d
e
l’
s
ab
ilit
y
to
h
elp
id
en
tify
d
e
p
r
ess
ed
s
y
m
p
to
m
s
,
in
clu
d
in
g
e
x
p
er
ien
ci
n
g
s
ad
n
e
s
s
,
d
im
in
is
h
ed
in
ter
est,
s
leep
d
is
tu
r
b
an
ce
s
,
an
d
s
u
icid
al
id
e
atio
n
s
in
th
e
u
r
b
a
n
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Evaluation Warning : The document was created with Spire.PDF for Python.