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v
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I
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u
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a
l
.
[
1
7
]
,
t
h
e
p
e
r
f
o
r
m
a
n
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o
f
t
w
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p
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ct
r
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r
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b
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H
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m
o
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l
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,
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l
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R
GB
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a
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h
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.
A
n
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T
a
j
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i
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,
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t
a
l
.
[
1
8
]
,
p
r
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pr
o
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s
s
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n
g
t
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c
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q
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N
et
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h
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as
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o
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h
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r
a
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d
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T
h
i
s
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s
ea
r
ch
s
t
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a
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o
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DL
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d
d
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t
h
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m
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o
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a
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l
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t
o
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m
p
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o
n
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o
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a
t
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c
a
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e
r
i
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h
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a
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l
y
s
t
a
g
e
.
T
h
e
p
ap
e
r
i
s
s
t
r
u
c
t
u
r
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d
as
f
o
l
l
o
w
s
.
I
n
t
h
e
n
e
x
t
s
e
ct
i
o
n
,
t
h
e
p
r
o
p
o
s
e
d
a
p
p
r
o
a
c
h
i
s
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ep
r
e
s
e
n
t
e
d
,
w
h
e
r
e
d
et
a
i
ls
o
f
th
e
a
r
c
h
i
t
e
c
t
u
r
e
a
n
d
m
e
t
h
o
d
o
l
o
g
y
a
r
e
d
i
s
c
u
s
s
e
d
.
T
h
i
s
s
e
c
t
i
o
n
al
s
o
p
r
es
e
n
ts
m
o
d
e
l
s
u
n
d
e
r
i
n
v
es
t
i
g
at
i
o
n
,
d
a
t
ase
t
s
,
a
n
d
e
v
al
u
a
t
i
o
n
m
e
t
r
i
c
s
.
S
e
ct
i
o
n
3
p
r
e
s
e
n
ts
e
x
p
e
r
i
m
e
n
t
a
l
r
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u
l
ts
a
n
d
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o
m
p
a
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s
o
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s
d
o
n
e
w
it
h
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o
r
k
s
f
o
u
n
d
i
n
t
h
e
l
i
t
e
r
at
u
r
e
.
I
n
s
e
c
ti
o
n
4
,
c
o
n
c
l
u
s
i
o
n
s
a
r
e
d
i
s
cu
s
s
e
d
.
2.
P
R
O
P
O
SE
D
M
E
T
H
O
DO
L
O
G
Y
T
h
e
tr
ain
in
g
p
r
o
ce
s
s
o
f
d
ee
p
n
etwo
r
k
s
to
r
ec
o
g
n
ize
p
a
tter
n
s
in
d
ata
an
d
m
ak
e
d
e
cisi
o
n
s
o
r
p
r
ed
ictio
n
s
b
ased
o
n
d
etec
ted
p
atter
n
s
is
ce
n
tr
al
to
ML
.
T
h
e
DL
m
o
d
els
ar
e
s
tatis
tical
an
d
allo
w
in
v
esti
g
ato
r
s
to
ev
alu
ate
th
e
p
e
r
f
o
r
m
an
ce
o
f
th
e
m
o
d
el
af
ter
lear
n
in
g
f
r
o
m
av
ailab
le
d
ata
.
As
lab
eled
d
atas
ets
ar
e
n
o
w
ea
s
ily
ac
ce
s
s
ib
le
in
th
e
p
u
b
lic
d
o
m
ain
,
s
ev
er
al
lear
n
in
g
m
o
d
els
h
av
e
b
ee
n
p
u
b
lis
h
ed
i
n
th
e
liter
atu
r
e
with
claim
ed
ac
cu
r
ac
y
r
elate
d
t
o
s
k
in
ca
n
ce
r
d
etec
tio
n
r
ea
ch
in
g
9
0
%
o
n
s
elec
ted
d
atasets
.
W
ith
th
e
av
ailab
ilit
y
o
f
h
ig
h
-
p
o
wer
c
o
m
p
u
tatio
n
al
m
a
ch
in
es,
it
s
ee
m
s
ea
s
y
to
v
alid
ate
th
e
claim
ed
ac
c
u
r
ac
y
o
n
a
g
iv
en
d
ataset.
B
u
t
th
e
is
s
u
es
f
ac
ed
ar
e
m
an
y
.
T
h
e
f
o
r
em
o
s
t
is
th
e
tr
ain
in
g
o
f
c
o
m
p
lex
m
o
d
els
o
n
lar
g
e
d
atasets
.
T
h
is
tak
es
a
lo
t
o
f
tim
e,
as
m
o
s
t
o
f
th
e
tim
e
th
e
r
eso
u
r
ce
s
ar
e
s
h
ar
ed
am
o
n
g
s
t
u
s
er
s
.
Nex
t,
s
o
m
etim
es
it
is
n
o
t
p
o
s
s
ib
le
to
f
in
d
m
o
d
els th
at
ar
e
test
ed
o
n
m
o
r
e
th
an
o
n
e
d
ataset.
I
n
th
is
r
esear
ch
,
th
e
m
eth
o
d
o
lo
g
y
is
to
in
v
esti
g
ate
a
s
et
o
f
lear
n
in
g
m
o
d
els
(
lik
e
C
NN
s
eq
u
en
tial,
I
n
ce
p
tio
n
V
3
,
R
esNet5
0
,
an
d
Xce
p
tio
n
)
,
wh
ich
ar
e
s
elec
t
ed
b
ased
o
n
th
eir
p
er
f
o
r
m
an
ce
o
n
s
k
in
ca
n
ce
r
d
etec
tio
n
.
T
o
s
av
e
tr
ain
in
g
tim
e,
th
eir
p
er
f
o
r
m
an
ce
is
ca
lcu
lated
b
ased
o
n
p
h
ases
to
o
p
tim
ize
th
e
co
m
p
u
tatio
n
al
co
s
t
v
er
s
u
s
s
elec
ted
m
o
d
els.
I
n
th
e
f
ir
s
t
p
h
a
s
e,
a
b
alan
ce
d
d
ataset
(
d
ataset
1
)
is
em
p
lo
y
ed
to
tr
ain
lear
n
i
n
g
m
o
d
els
f
o
r
p
er
f
o
r
m
an
ce
.
Nex
t,
th
e
tr
ain
ed
m
o
d
els
ar
e
cr
o
s
s
-
v
alid
ated
a
n
d
test
ed
b
ased
o
n
p
er
f
o
r
m
an
ce
m
etr
ics.
So
m
e
o
f
th
e
lear
n
in
g
m
o
d
els
in
th
is
p
h
ase
ar
e
d
r
o
p
p
ed
d
u
e
to
p
o
o
r
p
er
f
o
r
m
an
ce
,
an
d
th
e
r
est m
o
v
e
o
n
t
o
th
e
n
e
x
t p
h
ase.
I
n
th
e
s
ec
o
n
d
p
h
ase,
a
s
u
b
s
et
o
f
a
lar
g
e
d
ataset
(
d
ataset
2
)
is
u
s
ed
to
ass
ess
th
e
g
en
er
alize
d
p
er
f
o
r
m
a
n
ce
o
f
th
e
s
elec
ted
m
o
d
els.
T
h
e
b
etter
-
p
er
f
o
r
m
in
g
m
o
d
els
in
th
is
p
h
ase
en
ter
th
e
last
s
tag
e,
wh
er
e
th
eir
g
e
n
er
alize
d
p
er
f
o
r
m
an
ce
is
in
v
esti
g
ated
o
n
th
e
f
u
ll
d
ataset
(
d
ataset
2
)
.
T
h
e
m
eth
o
d
o
lo
g
y
is
d
ep
icted
in
Fig
u
r
e
1
.
T
h
e
lo
ad
ed
d
ataset
1
n
ee
d
s
to
b
e
p
r
ep
r
o
ce
s
s
ed
an
d
lab
eled
b
ef
o
r
e
b
ein
g
s
u
p
p
lied
to
alg
o
r
ith
m
s
f
o
r
m
o
d
el
b
u
ild
in
g
.
I
t
was
m
ad
e
s
u
r
e
th
at
th
e
d
ataset
ch
o
s
en
f
o
r
th
e
m
o
d
el
was
b
alan
ce
d
f
o
r
a
cc
u
r
ate
p
r
ed
ictio
n
.
I
n
th
e
f
ir
s
t
p
h
ase,
f
o
u
r
alg
o
r
it
h
m
s
f
r
eq
u
e
n
tly
r
ep
o
r
ted
in
th
e
liter
atu
r
e
f
o
r
s
k
in
ca
n
ce
r
cla
s
s
if
icatio
n
ar
e
to
b
e
tr
ain
ed
,
cr
o
s
s
-
v
alid
ated
,
an
d
t
ested
b
ef
o
r
e
b
ei
n
g
d
ec
lar
e
d
s
u
itab
le
f
o
r
f
u
r
th
er
i
n
v
esti
g
atio
n
o
n
g
e
n
er
aliza
tio
n
.
T
h
e
cr
iter
io
n
ch
o
s
en
f
o
r
th
e
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
e
was
class
if
icatio
n
ac
cu
r
ac
y
.
I
n
t
h
e
n
ex
t
p
h
ase,
th
e
ch
o
s
en
m
o
d
el(
s
)
ar
e
s
elec
ted
f
o
r
g
en
e
r
aliza
tio
n
,
i.e
.
,
th
ey
a
r
e
tr
ain
e
d
o
n
a
b
ala
n
ce
d
s
u
b
s
et
o
f
a
la
r
g
er
d
ataset
(
d
ataset
2
)
.
T
h
e
p
er
f
o
r
m
an
ce
m
ea
s
u
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o
d
els,
d
ataset
2
(
HAM
1
0
0
0
0
)
was
em
p
lo
y
ed
.
T
o
a
v
o
id
C
PU
cr
ash
es
d
u
e
to
h
ea
v
y
co
m
p
u
tatio
n
s
o
n
b
o
th
th
e
I
n
ce
p
tio
n
V
3
an
d
Xce
p
tio
n
m
o
d
els,
a
b
alan
ce
d
s
u
b
s
et
(
3
2
5
0
im
a
g
es)
o
f
t
h
e
HAM
1
0
0
0
d
ataset
was
ch
o
s
en
to
tr
ain
th
e
I
n
ce
p
t
io
n
V
3
a
n
d
Xce
p
tio
n
m
o
d
els,
an
d
a
b
alan
ce
d
s
et
o
f
1
0
0
0
im
ag
es
was
em
p
lo
y
ed
f
o
r
test
in
g
b
o
t
h
m
o
d
els.
T
h
e
m
o
d
els
ca
r
r
ied
th
e
s
am
e
p
ar
am
eter
s
,
a
n
d
th
e
r
esu
ltin
g
tr
ain
in
g
ac
cu
r
ac
y
t
u
r
n
e
d
o
u
t
to
b
e
9
4
.
5
1
an
d
9
7
.
8
5
%
f
o
r
th
e
I
n
ce
p
tio
n
V
3
an
d
Xce
p
ti
o
n
m
o
d
els,
r
esp
ec
tiv
ely
,
a
n
d
test
in
g
ac
cu
r
ac
y
o
f
8
6
.
9
a
n
d
8
9
.
4
%
f
o
r
th
e
I
n
ce
p
tio
n
V
3
an
d
Xce
p
tio
n
m
o
d
els.
T
h
e
r
esu
lts
ar
e
s
h
o
wn
in
T
ab
le
2
.
T
h
e
r
esu
lts
s
u
g
g
est
th
at
th
e
Xce
p
tio
n
m
o
d
el'
s
p
er
f
o
r
m
an
ce
is
s
u
p
er
io
r
to
th
e
I
n
ce
p
tio
n
V
3
m
o
d
el
f
o
r
s
k
in
ca
n
ce
r
class
if
icatio
n
.
T
h
e
r
esu
ltin
g
c
o
n
f
u
s
io
n
m
atr
ix
s
h
o
ws v
alu
es
o
f
8
9
.
4
,
9
7
.
1
,
8
1
.
2
,
a
n
d
8
8
.
4
%
f
o
r
ac
c
u
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e,
r
esp
ec
tiv
ely
.
3
.3
.
S
i
mu
l
a
t
i
o
n
3
T
o
in
v
esti
g
ate
f
u
r
t
h
er
,
th
e
wh
o
le
HAM
1
0
0
0
0
d
ataset
was
em
p
lo
y
ed
to
ass
ess
th
e
g
en
e
r
alize
d
ac
cu
r
ac
y
p
e
r
f
o
r
m
an
ce
o
f
th
e
Xce
p
tio
n
3
m
o
d
el
with
t
h
e
s
am
e
p
ar
am
eter
s
.
T
h
e
r
esu
ltin
g
ac
cu
r
ac
y
o
f
th
e
Xce
p
tio
n
m
o
d
el
f
o
r
s
k
in
ca
n
ce
r
class
if
icatio
n
tu
r
n
ed
o
u
t
to
b
e
9
8
an
d
9
2
.
3
%
f
o
r
tr
ain
in
g
an
d
test
in
g
,
r
esp
ec
tiv
ely
.
T
h
e
r
esu
ltin
g
a
cc
u
r
ac
y
g
r
ap
h
is
s
h
o
wn
i
n
Fig
u
r
e
3
;
Fig
u
r
e
3
(
a
)
s
h
o
ws
a
cc
u
r
ac
y
o
n
th
e
HAM
1
0
0
0
0
s
u
b
s
et
an
d
Fig
u
r
e
3
(
b
)
s
h
o
ws
a
c
c
u
r
a
c
y
o
n
t
h
e
f
u
l
l
d
a
t
a
s
et
.
Fo
r
co
m
p
ar
is
o
n
p
u
r
p
o
s
es,
th
e
ac
c
u
r
ac
y
b
ased
o
n
test
in
g
1
0
0
0
im
a
g
es
(
f
r
o
m
s
im
u
latio
n
2
)
was
also
co
m
p
u
ted
an
d
is
also
p
l
o
tted
in
Fig
u
r
e
3
.
B
o
th
g
r
ap
h
s
s
u
g
g
est
th
at
in
cr
ea
s
in
g
th
e
d
ataset
im
p
r
o
v
ed
m
o
d
el
ac
cu
r
ac
y
,
an
d
r
ea
f
f
ir
m
ed
th
e
s
u
p
er
io
r
g
en
er
alize
d
p
er
f
o
r
m
an
ce
o
f
th
e
Xce
p
tio
n
m
o
d
el.
Fu
r
t
h
er
,
t
h
e
r
esu
lts
o
f
t
h
is
r
esear
ch
wer
e
c
o
m
p
a
r
ed
w
ith
r
ec
en
t
liter
atu
r
e
o
n
s
k
in
ca
n
ce
r
class
if
icatio
n
em
p
lo
y
in
g
d
if
f
er
en
t
d
atasets
,
an
d
ar
e
d
is
p
lay
ed
in
T
a
b
le
3
.
T
h
e
co
m
p
ar
ativ
e
r
esu
lts
s
h
o
w
th
e
b
etter
p
er
f
o
r
m
an
ce
o
f
t
h
e
Xce
p
tio
n
m
o
d
el
o
v
er
m
u
ltip
le
d
atasets
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
1
4
I
n
t J Ad
v
Ap
p
l Sci
,
Vo
l.
1
4
,
No
.
1
,
Ma
r
c
h
2
0
2
5
:
69
-
76
74
(
a
)
(
b
)
(
c
)
F
i
g
u
r
e
2
.
T
r
a
i
n
i
n
g
a
c
c
u
r
a
c
y
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f
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a
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C
N
N
s
e
q
u
e
n
ti
a
l
,
(
b
)
R
e
s
N
et
5
0
,
a
n
d
(
c
)
X
c
e
p
t
i
o
n
(
a
)
(
b
)
F
i
g
u
r
e
3
.
A
c
c
u
r
a
c
y
o
n
(
a
)
H
AM
1
0
0
0
0
s
u
b
s
e
t
a
n
d
(
b
)
f
u
l
l
d
a
ta
s
e
t
T
a
b
l
e
1
.
A
c
c
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r
a
c
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o
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m
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d
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l
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f
i
r
s
t
d
at
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et
M
o
d
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l
T
r
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i
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e
s
t
i
n
g
C
N
N
7
8
.
5
%
6
9
.
5
3
%
R
e
s
N
e
t
5
0
9
6
.
9
2
%
8
2
.
8
8
%
I
n
c
e
p
t
i
o
n
V3
9
3
.
4
5
%
8
6
.
7
%
X
c
e
p
t
i
o
n
9
7
.
8
4
%
8
6
.
9
%
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ad
v
Ap
p
l Sci
I
SS
N:
2252
-
8
8
1
4
E
n
h
a
n
ce
d
s
kin
ca
n
ce
r
cla
s
s
ifi
ca
tio
n
via
X
ce
p
tio
n
mo
d
el
(
Qu
r
b
a
n
A
li
Memo
n
)
75
T
a
b
l
e
2
.
M
o
d
e
l
a
c
c
u
r
a
c
y
o
n
a
s
u
b
s
e
t
o
f
t
h
e
H
A
M
1
0
0
0
0
d
a
t
a
s
et
M
o
d
e
l
T
r
a
i
n
i
n
g
T
e
s
t
i
n
g
I
n
c
e
p
t
i
o
n
V3
9
4
.
5
1
%
8
6
.
9
%
X
c
e
p
t
i
o
n
9
7
.
8
5
%
8
9
.
4
%
T
a
b
l
e
3
.
C
o
m
p
a
r
is
o
n
o
f
m
o
d
e
l
s
b
a
s
e
d
o
n
a
c
c
u
r
a
c
y
S
o
u
r
c
e
D
a
t
a
s
e
t
u
s
e
d
A
c
c
u
r
a
c
y
W
h
e
t
h
e
r
g
e
n
e
r
a
l
i
z
e
d
?
M
r
i
d
h
a
e
t
a
l
.
[
1
6
]
H
A
M
1
0
0
0
0
8
2
.
0
%
No
H
u
a
n
g
e
t
a
l
.
[
1
7
]
I
S
I
C
7
9
.
2
%
No
T
a
j
e
r
i
a
n
e
t
a
l
.
[
1
8
]
H
A
M
1
0
0
0
0
8
4
.
3
%
No
A
l
i
e
t
a
l
.
[
2
6
]
H
A
M
1
0
0
0
0
9
1
.
9
3
%
No
P
r
o
p
o
s
e
d
H
A
M
1
0
0
0
0
9
2
.
9
3
%
Y
e
s
4.
C
O
N
CL
US
I
O
N
T
h
is
r
esear
ch
ev
alu
ated
m
u
lti
p
le
D
L
m
o
d
els
o
n
a
b
alan
ce
d
d
ataset,
with
th
e
to
p
-
p
er
f
o
r
m
in
g
m
o
d
el
f
u
r
th
er
tr
ain
ed
o
n
a
lar
g
e
r
d
at
aset
to
ass
ess
g
en
er
aliza
tio
n
.
T
o
im
p
r
o
v
e
co
m
p
u
tatio
n
al
ef
f
icien
cy
,
a
s
u
b
s
et
o
f
th
is
lar
g
er
d
ataset
was
u
s
ed
f
o
r
ev
alu
atio
n
,
ex
clu
d
in
g
less
ef
f
ec
tiv
e
m
o
d
els.
T
h
e
Xce
p
tio
n
m
o
d
el
ex
ce
lled
,
ac
h
iev
in
g
9
9
% a
cc
u
r
ac
y
in
tr
a
in
in
g
an
d
9
3
% in
test
in
g
.
Desp
ite
u
s
in
g
o
n
ly
a
f
ew
tr
ain
in
g
ep
o
ch
s
,
th
e
m
o
d
el’
s
p
er
f
o
r
m
an
ce
co
u
ld
p
o
ten
tially
b
e
im
p
r
o
v
e
d
with
h
y
p
er
p
a
r
am
eter
tu
n
i
n
g
.
C
o
m
p
ar
is
o
n
s
s
u
g
g
est
th
is
m
o
d
el
o
u
tp
er
f
o
r
m
s
o
t
h
er
r
ec
en
t
s
tu
d
ies.
T
h
e
r
esu
lts
o
f
th
is
m
o
d
el
ar
e
lik
el
y
to
en
h
a
n
ce
s
t
an
d
ar
d
izatio
n
an
d
r
eg
u
lar
izatio
n
ac
tiv
ities
.
Stan
d
ar
d
izatio
n
in
s
k
in
ca
n
ce
r
d
etec
tio
n
is
g
u
id
ed
b
y
d
er
m
at
o
lo
g
y
an
d
m
ed
ical
im
ag
in
g
in
itiativ
es.
Key
e
f
f
o
r
ts
in
clu
d
e
d
ev
elo
p
in
g
p
r
o
to
co
ls
,
g
u
i
d
elin
es,
an
d
b
e
n
ch
m
ar
k
s
to
a
d
v
an
ce
tech
n
o
lo
g
y
.
T
h
e
I
SIC
o
r
g
an
iz
atio
n
co
n
tr
i
b
u
tes
b
y
o
f
f
e
r
in
g
a
d
atab
ase
o
f
clin
ical
an
d
d
er
m
o
s
co
p
ic
im
ag
es
an
d
o
r
g
an
izin
g
r
esear
ch
c
h
allen
g
e
s
.
R
eg
u
lato
r
y
b
o
d
ies
lik
e
th
e
E
u
r
o
p
ea
n
Me
d
ic
in
es
Ag
en
c
y
an
d
th
e
Fo
o
d
an
d
Dr
u
g
Ad
m
in
is
tr
atio
n
(
FDA
)
estab
lis
h
s
tan
d
ar
d
s
f
o
r
m
ed
ical
d
ev
ices
an
d
test
in
g
to
en
s
u
r
e
co
m
p
lian
ce
a
n
d
ef
f
ec
tiv
en
ess
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
a
u
t
h
o
r
s
w
is
h
t
o
t
h
a
n
k
U
n
ite
d
A
r
a
b
E
m
i
r
a
t
es
U
n
i
v
e
r
s
i
t
y
f
o
r
S
UR
E
P
L
U
S
G
r
a
n
t
N
o
.
G
4
3
5
6
,
2
023.
RE
F
E
R
E
NC
E
S
[
1
]
Y
.
D
a
i
e
t
a
l
.
,
“
W
e
a
r
a
b
l
e
s
e
n
s
o
r
p
a
t
c
h
w
i
t
h
h
y
d
r
o
g
e
l
m
i
c
r
o
n
e
e
d
l
e
s
f
o
r
i
n
s
i
t
u
a
n
a
l
y
si
s
o
f
i
n
t
e
r
s
t
i
t
i
a
l
f
l
u
i
d
,”
AC
S
A
p
p
l
i
e
d
M
a
t
e
ri
a
l
s
& In
t
e
rf
a
c
e
s
,
v
o
l
.
1
5
,
n
o
.
4
9
,
D
e
c
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
2
1
/
a
c
s
a
mi
.
3
c
1
2
7
4
0
.
[
2
]
B
.
A
sa
d
i
a
n
d
Q
.
A
.
M
e
m
o
n
,
“
La
y
e
r
e
d
d
e
e
p
l
e
a
r
n
i
n
g
f
o
r
i
m
p
r
o
v
e
d
b
r
e
a
s
t
c
a
n
c
e
r
d
e
t
e
c
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