Multi-Label Classification on CheXpert

Metric: NUM RADS BELOW CURVE (higher is better)

LeaderboardDataset

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Results

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#	Model↕	NUM RADS BELOW CURVE▼	Augmentations	Paper	Date↕	Code
1	inisis	3	No	-	-	-
2	JF aboy ensemble_V2 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng	3	No	-	-	-
3	DeepAUC-v1	2.8	No	Large-scale Robust Deep AUC Maximization: A New ...	2020-12-06	Code
4	YWW(ensemble)	2.8	No	-	-	-
5	as-hust-v2	2.8	No	-	-	-
6	Hierarchical-Learning-V1 (ensemble)	2.6	No	Interpreting chest X-rays via CNNs that exploit ...	2019-11-15	Code
7	Conditional-Training-LSR	2.6	No	-	-	-
8	Hierarchical-Learning-V4 (ensemble)	2.6	No	Interpreting chest X-rays via CNNs that exploit ...	2019-11-15	Code
9	Conditional-Training-LSR-V1	2.6	No	-	-	-
10	Hierarchical-Learning-V0 (ensemble)	2.6	No	-	-	-
11	Multi-Stage-Learning-CNN-V3 (ensemble)	2.6	No	-	-	-
12	DeepCNNsGM(ensemble)	2.6	No	-	-	-
13	DeepCNNs(ensemble)	2.6	No	-	-	-
14	SenseXDR	2.6	No	-	-	-
15	ihil (ensemble)	2.6	No	-	-	-
16	DRNet (ensemble)	2.6	No	-	-	-
17	yw	2.6	No	-	-	-
18	Anatomy-XNet-V1	2.6	No	Anatomy-XNet: An Anatomy Aware Convolutional Neu...	2021-06-10	-
19	uest	2.6	No	-	-	-
20	DE_APR ensemble ltt	2.6	No	-	-	-
21	DE_APR_N ensemble ltt	2.6	No	-	-	-
22	Multi-Stage-Learning-CNN-V2 (ensemble)	2.6	No	-	-	-
23	Weighted-CNN(ensemble)	2.6	No	-	-	-
24	zjr(ensembel)	2.6	No	-	-	-
25	{"submit_id": "0x3c7b0af1b5784c159daf259c58543aa3", "predict_id": "0x67b23473183f4f43afa3b37edbc5d7fe", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	2.6	No	-	-	-
26	BDNB	2.6	No	-	-	-
27	JF Coolver ensemble	2.6	No	-	-	-
28	DE_JUN4_RS_EN ensemble LTT	2.6	No	-	-	-
29	Mehdi_You (ensemble)	2.6	No	-	-	-
30	A Good Model (single model) Macao Polytechnic University	2.6	No	-	-	Code
31	A Good Model (single model)	2.6	No	-	-	-
32	Anatomy-XNet (ensemble)	2.6	No	Anatomy-XNet: An Anatomy Aware Convolutional Neu...	2021-06-10	-
33	desmond	2.6	No	-	-	-
34	DE_JUN1_RS_EN ensemble LTT	2.6	No	-	-	-
35	TGNB	2.6	No	-	-	-
36	DE_JUN2_RS_EN ensemble LTT	2.6	No	-	-	-
37	hoanganh_VB_ensemble3	2.4	No	-	-	-
38	alimebkovk	2.4	No	-	-	-
39	Hoang_VB_ensemble31_v	2.4	No	-	-	-
40	tedtt	2.4	No	-	-	-
41	as-hust-v3	2.4	No	-	-	-
42	hoanganh_VB_VN	2.4	No	-	-	-
43	Hierarchical-CNN-Ensemble-V1 (ensemble)	2.4	No	-	-	-
44	hoanganhcnu_ensemble27_v	2.4	No	-	-	-
45	YJ&&YWW :https://github.com/inisis/chexper	2.4	No	-	-	-
46	as-hust-v1	2.4	No	-	-	-
47	Maxium (ensemble)	2.4	No	-	-	-
48	Average-CNN(ensemble)	2.4	No	-	-	-
49	MaxAUC	2.4	No	-	-	-
50	SuperCNNv3	2.4	No	-	-	-
51	hyc	2.4	No	-	-	-
52	hoangnguyenkcv1	2.4	No	-	-	-
53	HOANG_VB_VN_2	2.4	No	-	-	-
54	thang ensemble colo	2.4	No	-	-	-
55	hoangnn9 ensemble VBV	2.4	No	-	-	-
56	JF aboy ensemble_V1 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng	2.4	No	-	-	-
57	Ensemble_v2	2.4	No	-	-	-
58	DE_JUN3_RS_EN ensemble LTT	2.4	No	-	-	-
59	{"submit_id": "0x57dc2989f0474ca095d0841df09cfb18", "predict_id": "0xd43bcf7d4c9b467894db2b274b18794e", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	2.4	No	-	-	-
60	ATT-AW-v1	2.4	No	-	-	-
61	ensemble SN	2.4	No	-	-	-
62	zhangjingyan	2.4	No	-	-	-
63	GRNB	2.4	No	-	-	-
64	{"submit_id": "0x33aeb0f2525e482a886196c273bdf1ba", "predict_id": "0xff2f60907da8440d98ff17f0af749535", "submitter_id": "0x0b382a226d4548c9b441f19b1907fe0f"	2.2	No	-	-	-
65	brian-baseline-v2	2.2	No	-	-	-
66	Deep-CNNs-V1	2.2	No	-	-	-
67	vdn6 ensemble ltt	2.2	No	-	-	-
68	Overfit ensemble OTH-A	2.2	No	-	-	-
69	{"submit_id": "0xeb9c9e79ed9e4410a2a37d62322f4585", "predict_id": "0x735b718280b14e83895decbc31641f87", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	2.2	No	-	-	-
70	Multi-Stage-Learning-CNN-V0	2.2	No	-	-	-
71	Deadpoppy Ensemble	2.2	No	-	-	-
72	hoangnguyenkcv-ensemble28	2.2	No	-	-	-
73	Sky-Model	2.2	No	-	-	-
74	JF Deadpoppy	2.2	No	-	-	-
75	zjy	2.2	No	-	-	-
76	KCV-CNN-ensemble-CN	2.2	No	-	-	-
77	songta	2.2	No	-	-	-
78	bhtrun	2.2	No	-	-	-
79	anatomy_xnet_v1 (single model)	2.2	No	-	-	-
80	ensemble SNU	2.2	No	-	-	-
81	HinaNetV2 (ensemble)	2.2	No	-	-	-
82	thangbk(ensemble)	2	No	-	-	-
83	Deep-CNNs (ensemble)	2	No	-	-	-
84	YWW-YJ:https://github.com/inisis/chexper	2	No	-	-	-
85	WL_Baseline (ensemble)	2	No	-	-	-
86	DS_APR_N single model ltt	2	No	-	-	-
87	DS_APR single model LTT	2	No	-	-	-
88	brian-baseline	2	No	-	-	-
89	KD-Prune10 (Single model)	2	No	-	-	-
90	guran_ri	2	No	-	-	-
91	Multi-CNN	2	No	-	-	-
92	Max (single model)	2	No	-	-	-
93	{AVG_MAX}(ensemble)	2	No	-	-	-
94	G_Mans_ensembl	1.8	No	-	-	-
95	vdnnn (ensemble)	1.8	No	-	-	-
96	BAAZT	1.8	No	-	-	-
97	Stanford Baseline (ensemble)	1.8	No	CheXpert: A Large Chest Radiograph Dataset with ...	2019-01-21	Code
98	hy	1.8	No	-	-	-
99	DeepLungsEnsemble	1.8	No	-	-	-
100	Z_Ensemble_	1.8	No	-	-	-
101	BUA	1.8	No	-	-	-
102	Deadpoppy Single	1.8	No	-	-	-
103	vbn (single model)	1.6	No	-	-	-
104	muti_base (ensemble)	1.6	No	-	-	-
105	{ForwardModelEnsembleCorrected} (ensemble)	1.6	No	-	-	-
106	LBC-v2 (ensemble)	1.6	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
107	LBC-v2	1.6	No	-	-	-
108	LBC-v2 (ensemble)	1.6	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
109	ForwardMECorrectedFull (ensemble)	1.6	No	-	-	-
110	Orlando (single model)	1.6	No	-	-	-
111	Ensemble_v1	1.6	No	-	-	-
112	MLC11 NotDense (single-model)	1.6	No	-	-	-
113	llllldz	1.6	No	-	-	-
114	DiseaseNet Samg2003 single model, UIUC, http://sambhavgupta.com	1.6	No	-	-	-
115	DiseaseNet Samg2003 single model, DPS RKP, http://sambhavgupta.co	1.6	No	-	-	-
116	ForwardModelEnsemble (ensemble)	1.6	No	-	-	-
117	NewTrickTest (ensemble)	1.6	No	-	-	-
118	ylz-v01	1.6	No	-	-	-
119	adoudo	1.6	No	-	-	-
120	MM1	1.6	No	-	-	-
121	hycN	1.6	No	-	-	-
122	zhujier	1.6	No	-	-	-
123	HybridModelEnsemble (ensemble)	1.6	No	-	-	-
124	MNet-Fix (Single Model)	1.6	No	-	-	-
125	Z_Ensemble_V	1.4	No	-	-	-
126	Nakajima_ayas	1.4	No	-	-	-
127	LBC-v0	1.4	No	-	-	-
128	LBC-v0 (ensemble)	1.4	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
129	LBC-v0 (ensemble)	1.4	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
130	G_Mans_v2 (single model): LibAUC + coat_mini	1.4	No	-	-	-
131	ldz	1.4	No	-	-	-
132	Densenet	1.4	No	-	-	-
133	Stellarium-CheXpert-Local (single model)	1.4	No	-	-	-
134	Stellarium-CheXpert-Local	1.4	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
135	Stellarium-CheXpert-Local	1.4	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
136	{koala-large} (single model)	1.4	No	-	-	-
137	DenseNet169 at 320x320 (single model)	1.4	No	-	-	-
138	LR-baseline (ensemble)	1.4	No	-	-	-
139	JustAnotherDensenet	1.2	No	-	-	-
140	vn_2 single_model ltt	1.2	No	-	-	-
141	ljc226	1.2	No	-	-	-
142	AccidentNet v1 (single model)	1.2	No	-	-	-
143	MVD121	1.2	No	-	-	-
144	MVD121-320	1.2	No	-	-	-
145	Xception (single model)	1.2	No	-	-	-
146	Stellarium (single model)	1.2	No	-	-	-
147	Stellarium	1.2	No	-	-	-
148	pm_rn50_0.15pp	1.2	No	-	-	-
149	baseline3	1.2	No	-	-	-
150	Naive Densenet	1.2	No	-	-	-
151	{densenet} (single model)	1.2	No	-	-	-
152	DenseNet	1.2	No	-	-	-
153	MLGCN (single model)	1.2	No	-	-	-
154	hust(single model)	1	No	-	-	-
155	U-Random-Ind (single)	1	No	-	-	-
156	ylz-v02	1	No	-	-	-
157	pause	1	No	-	-	-
158	Overfit ensemble OT	1	No	-	-	-
159	DataAugFTW (single model)	1	No	-	-	-
160	{koala} (single model)	1	No	-	-	-
161	PrateekMunja	1	No	-	-	-
162	AccidentNet V2 (single model)	1	No	-	-	-
163	HCL1 (single model)	1	No	-	-	-
164	GCN_densenet121-single mode	1	No	-	-	-
165	{GoDense} (single model)	1	No	-	-	-
166	baseline2	1	No	-	-	-
167	Haruka_Hamasak	0.8	No	-	-	-
168	MVR50	0.8	No	-	-	-
169	Coolver XH	0.8	No	-	-	-
170	Aoitori (single model)	0.8	No	-	-	-
171	GreenTeaCalpis (single model)	0.8	No	-	-	-
172	baseline1 (single model)	0.8	No	-	-	-
173	Densenet-Basic Single NUS	0.8	No	-	-	-
174	KD_Mobilenet (single model)	0.8	No	-	-	-
175	MLKD (Single model)	0.8	No	-	-	-
176	haw02 (single model)	0.8	No	-	-	-
177	mhealth_buet (single model)	0.6	No	-	-	-
178	{chexpert-classifier}(single model)	0.6	No	-	-	-
179	Yoake (single model)	0.6	No	-	-	-
180	MLC11 Baseline (single-model)	0.6	No	-	-	-
181	BASELINE ResNet50	0.6	No	-	-	-
182	Baseline DenseNet161	0.6	No	-	-	-
183	DSENet	0.6	No	-	-	-
184	BASELINE Acorn	0.6	No	-	-	-
185	ErrorNet (single model)	0.6	No	-	-	-
186	SleepNet (single model)	0.6	No	-	-	-
187	Model_Team_34 (single model)	0.6	No	-	-	-
188	model2_DenseNet121	0.6	No	-	-	-
189	G_Mans_v1 (single model):	0.6	No	-	-	-
190	haw-baseline (single model)	0.6	No	-	-	-
191	DearBrave (single model)	0.4	No	-	-	-
192	Multi-CNN (ensemble)	0.4	No	-	-	-
193	inceptionv3_single_NN	0.4	No	-	-	-
194	rayOfLightSingle (Single Model)	0.4	No	-	-	-
195	Test model habbe	0.4	No	-	-	-
196	HinaNet (single model)	0.4	No	-	-	-
197	mwowra-conditional (single)	0.4	No	-	-	-
198	multihead_model (one model for all pathologies)	0.4	No	-	-	-
199	MLC9_Densenet (single model)	0.4	No	-	-	-
200	Baseline	0.2	No	pyannote.audio: neural building blocks for speak...	2019-11-04	Code
201	singlehead_models (single model combined)	0.2	No	-	-	-
202	mobilenet (single model)	0.2	No	-	-	-
203	Grp12v2USup2OSamp (ensemble)	0.2	No	-	-	-
204	Chest-x-ray classification using	0.2	No	-	-	-
205	UMLS_CLIP (single model)	0	No	-	-	-
206	CombinedTrainDenseNet121 (single model)	0	No	-	-	-
207	Grp12BigCNN	0	No	-	-	-
208	DNET121-single	0	No	-	-	-
209	12ASLv2(single)	0	No	-	-	-
210	DenseNet121 (single model)	0	No	-	-	-
211	12ASLv1(single)	0	No	-	-	-
212	rayOfLight (ensemble)	0	No	-	-	-
213	BASELINE DenseNet121	0	No	-	-	-
214	BME_Final_v2	0	No	-	-	-
215	{densenet121}{single model	0	No	-	-	-
216	autobot	0	No	-	-	-
217	{MLC02_DenseNet121}	0	No	-	-	-
218	efficiantB5 (single model)	0	No	-	-	-
219	apalepu1	0	No	-	-	-
220	Erdem (single)	0	No	-	-	-
221	Adalab Standard (Single Model)	0	No	-	-	-
222	Adalab Standard (single model)	0	No	-	-	-
223	zeroshot_medclip_baseline (ensemble)	0	No	-	-	-

#1inisis
3
NUM RADS BELOW CURVE
No paper
#2JF aboy ensemble_V2 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng
3
NUM RADS BELOW CURVE
No paper
#3DeepAUC-v1SOTA
2.8
NUM RADS BELOW CURVE· 2020-12-06
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification Code
#4YWW(ensemble)
2.8
NUM RADS BELOW CURVE
No paper
#5as-hust-v2
2.8
NUM RADS BELOW CURVE
No paper
#6Hierarchical-Learning-V1 (ensemble)SOTA
2.6
NUM RADS BELOW CURVE· 2019-11-15
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels Code
#7Conditional-Training-LSR
2.6
NUM RADS BELOW CURVE
No paper
#8Hierarchical-Learning-V4 (ensemble)
2.6
NUM RADS BELOW CURVE· 2019-11-15
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels Code
#9Conditional-Training-LSR-V1
2.6
NUM RADS BELOW CURVE
No paper
#10Hierarchical-Learning-V0 (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#11Multi-Stage-Learning-CNN-V3 (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#12DeepCNNsGM(ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#13DeepCNNs(ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#14SenseXDR
2.6
NUM RADS BELOW CURVE
No paper
#15ihil (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#16DRNet (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#17yw
2.6
NUM RADS BELOW CURVE
No paper
#18Anatomy-XNet-V1
2.6
NUM RADS BELOW CURVE· 2021-06-10
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
#19uest
2.6
NUM RADS BELOW CURVE
No paper
#20DE_APR ensemble ltt
2.6
NUM RADS BELOW CURVE
No paper
#21DE_APR_N ensemble ltt
2.6
NUM RADS BELOW CURVE
No paper
#22Multi-Stage-Learning-CNN-V2 (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#23Weighted-CNN(ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#24zjr(ensembel)
2.6
NUM RADS BELOW CURVE
No paper
#25{"submit_id": "0x3c7b0af1b5784c159daf259c58543aa3", "predict_id": "0x67b23473183f4f43afa3b37edbc5d7fe", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
2.6
NUM RADS BELOW CURVE
No paper
#26BDNB
2.6
NUM RADS BELOW CURVE
No paper
#27JF Coolver ensemble
2.6
NUM RADS BELOW CURVE
No paper
#28DE_JUN4_RS_EN ensemble LTT
2.6
NUM RADS BELOW CURVE
No paper
#29Mehdi_You (ensemble)
2.6
NUM RADS BELOW CURVE
No paper
#30A Good Model (single model) Macao Polytechnic University
2.6
NUM RADS BELOW CURVE
No paperCode
#31A Good Model (single model)
2.6
NUM RADS BELOW CURVE
No paper
#32Anatomy-XNet (ensemble)
2.6
NUM RADS BELOW CURVE· 2021-06-10
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
#33desmond
2.6
NUM RADS BELOW CURVE
No paper
#34DE_JUN1_RS_EN ensemble LTT
2.6
NUM RADS BELOW CURVE
No paper
#35TGNB
2.6
NUM RADS BELOW CURVE
No paper
#36DE_JUN2_RS_EN ensemble LTT
2.6
NUM RADS BELOW CURVE
No paper
#37hoanganh_VB_ensemble3
2.4
NUM RADS BELOW CURVE
No paper
#38alimebkovk
2.4
NUM RADS BELOW CURVE
No paper
#39Hoang_VB_ensemble31_v
2.4
NUM RADS BELOW CURVE
No paper
#40tedtt
2.4
NUM RADS BELOW CURVE
No paper
#41as-hust-v3
2.4
NUM RADS BELOW CURVE
No paper
#42hoanganh_VB_VN
2.4
NUM RADS BELOW CURVE
No paper
#43Hierarchical-CNN-Ensemble-V1 (ensemble)
2.4
NUM RADS BELOW CURVE
No paper
#44hoanganhcnu_ensemble27_v
2.4
NUM RADS BELOW CURVE
No paper
#45YJ&&YWW :https://github.com/inisis/chexper
2.4
NUM RADS BELOW CURVE
No paper
#46as-hust-v1
2.4
NUM RADS BELOW CURVE
No paper
#47Maxium (ensemble)
2.4
NUM RADS BELOW CURVE
No paper
#48Average-CNN(ensemble)
2.4
NUM RADS BELOW CURVE
No paper
#49MaxAUC
2.4
NUM RADS BELOW CURVE
No paper
#50SuperCNNv3
2.4
NUM RADS BELOW CURVE
No paper
#51hyc
2.4
NUM RADS BELOW CURVE
No paper
#52hoangnguyenkcv1
2.4
NUM RADS BELOW CURVE
No paper
#53HOANG_VB_VN_2
2.4
NUM RADS BELOW CURVE
No paper
#54thang ensemble colo
2.4
NUM RADS BELOW CURVE
No paper
#55hoangnn9 ensemble VBV
2.4
NUM RADS BELOW CURVE
No paper
#56JF aboy ensemble_V1 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng
2.4
NUM RADS BELOW CURVE
No paper
#57Ensemble_v2
2.4
NUM RADS BELOW CURVE
No paper
#58DE_JUN3_RS_EN ensemble LTT
2.4
NUM RADS BELOW CURVE
No paper
#59{"submit_id": "0x57dc2989f0474ca095d0841df09cfb18", "predict_id": "0xd43bcf7d4c9b467894db2b274b18794e", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
2.4
NUM RADS BELOW CURVE
No paper
#60ATT-AW-v1
2.4
NUM RADS BELOW CURVE
No paper
#61ensemble SN
2.4
NUM RADS BELOW CURVE
No paper
#62zhangjingyan
2.4
NUM RADS BELOW CURVE
No paper
#63GRNB
2.4
NUM RADS BELOW CURVE
No paper
#64{"submit_id": "0x33aeb0f2525e482a886196c273bdf1ba", "predict_id": "0xff2f60907da8440d98ff17f0af749535", "submitter_id": "0x0b382a226d4548c9b441f19b1907fe0f"
2.2
NUM RADS BELOW CURVE
No paper
#65brian-baseline-v2
2.2
NUM RADS BELOW CURVE
No paper
#66Deep-CNNs-V1
2.2
NUM RADS BELOW CURVE
No paper
#67vdn6 ensemble ltt
2.2
NUM RADS BELOW CURVE
No paper
#68Overfit ensemble OTH-A
2.2
NUM RADS BELOW CURVE
No paper
#69{"submit_id": "0xeb9c9e79ed9e4410a2a37d62322f4585", "predict_id": "0x735b718280b14e83895decbc31641f87", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
2.2
NUM RADS BELOW CURVE
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#70Multi-Stage-Learning-CNN-V0
2.2
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#71Deadpoppy Ensemble
2.2
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#72hoangnguyenkcv-ensemble28
2.2
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#73Sky-Model
2.2
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#74JF Deadpoppy
2.2
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#75zjy
2.2
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#76KCV-CNN-ensemble-CN
2.2
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#77songta
2.2
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#78bhtrun
2.2
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#79anatomy_xnet_v1 (single model)
2.2
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#80ensemble SNU
2.2
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#81HinaNetV2 (ensemble)
2.2
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#82thangbk(ensemble)
2
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#83Deep-CNNs (ensemble)
2
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#84YWW-YJ:https://github.com/inisis/chexper
2
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#85WL_Baseline (ensemble)
2
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#86DS_APR_N single model ltt
2
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#87DS_APR single model LTT
2
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#88brian-baseline
2
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#89KD-Prune10 (Single model)
2
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#90guran_ri
2
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#91Multi-CNN
2
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#92Max (single model)
2
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#93{AVG_MAX}(ensemble)
2
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#94G_Mans_ensembl
1.8
NUM RADS BELOW CURVE
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#95vdnnn (ensemble)
1.8
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#96BAAZT
1.8
NUM RADS BELOW CURVE
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#97Stanford Baseline (ensemble)SOTA
1.8
NUM RADS BELOW CURVE· 2019-01-21
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Code
#98hy
1.8
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#99DeepLungsEnsemble
1.8
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#100Z_Ensemble_
1.8
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#101BUA
1.8
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#102Deadpoppy Single
1.8
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#103vbn (single model)
1.6
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#104muti_base (ensemble)
1.6
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#105{ForwardModelEnsembleCorrected} (ensemble)
1.6
NUM RADS BELOW CURVE
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#106LBC-v2 (ensemble)
1.6
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#107LBC-v2
1.6
NUM RADS BELOW CURVE
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#108LBC-v2 (ensemble)
1.6
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#109ForwardMECorrectedFull (ensemble)
1.6
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#110Orlando (single model)
1.6
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#111Ensemble_v1
1.6
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#112MLC11 NotDense (single-model)
1.6
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#113llllldz
1.6
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#114DiseaseNet Samg2003 single model, UIUC, http://sambhavgupta.com
1.6
NUM RADS BELOW CURVE
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#115DiseaseNet Samg2003 single model, DPS RKP, http://sambhavgupta.co
1.6
NUM RADS BELOW CURVE
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#116ForwardModelEnsemble (ensemble)
1.6
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#117NewTrickTest (ensemble)
1.6
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#118ylz-v01
1.6
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#119adoudo
1.6
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#120MM1
1.6
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#121hycN
1.6
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#122zhujier
1.6
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#123HybridModelEnsemble (ensemble)
1.6
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#124MNet-Fix (Single Model)
1.6
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#125Z_Ensemble_V
1.4
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#126Nakajima_ayas
1.4
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#127LBC-v0
1.4
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#128LBC-v0 (ensemble)
1.4
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#129LBC-v0 (ensemble)
1.4
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#130G_Mans_v2 (single model): LibAUC + coat_mini
1.4
NUM RADS BELOW CURVE
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#131ldz
1.4
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#132Densenet
1.4
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#133Stellarium-CheXpert-Local (single model)
1.4
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#134Stellarium-CheXpert-Local
1.4
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#135Stellarium-CheXpert-Local
1.4
NUM RADS BELOW CURVE· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#136{koala-large} (single model)
1.4
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#137DenseNet169 at 320x320 (single model)
1.4
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#138LR-baseline (ensemble)
1.4
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#139JustAnotherDensenet
1.2
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#140vn_2 single_model ltt
1.2
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#141ljc226
1.2
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#142AccidentNet v1 (single model)
1.2
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#143MVD121
1.2
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#144MVD121-320
1.2
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#145Xception (single model)
1.2
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#146Stellarium (single model)
1.2
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#147Stellarium
1.2
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#148pm_rn50_0.15pp
1.2
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#149baseline3
1.2
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#150Naive Densenet
1.2
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#151{densenet} (single model)
1.2
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#152DenseNet
1.2
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#153MLGCN (single model)
1.2
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#154hust(single model)
1
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#155U-Random-Ind (single)
1
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#156ylz-v02
1
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#157pause
1
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#158Overfit ensemble OT
1
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#159DataAugFTW (single model)
1
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#160{koala} (single model)
1
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#161PrateekMunja
1
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#162AccidentNet V2 (single model)
1
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#163HCL1 (single model)
1
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#164GCN_densenet121-single mode
1
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#165{GoDense} (single model)
1
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#166baseline2
1
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#167Haruka_Hamasak
0.8
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#168MVR50
0.8
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#169Coolver XH
0.8
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#170Aoitori (single model)
0.8
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#171GreenTeaCalpis (single model)
0.8
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#172baseline1 (single model)
0.8
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#173Densenet-Basic Single NUS
0.8
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#174KD_Mobilenet (single model)
0.8
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#175MLKD (Single model)
0.8
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#176haw02 (single model)
0.8
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#177mhealth_buet (single model)
0.6
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#178{chexpert-classifier}(single model)
0.6
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#179Yoake (single model)
0.6
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#180MLC11 Baseline (single-model)
0.6
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#181BASELINE ResNet50
0.6
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#182Baseline DenseNet161
0.6
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#183DSENet
0.6
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#184BASELINE Acorn
0.6
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#185ErrorNet (single model)
0.6
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#186SleepNet (single model)
0.6
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#187Model_Team_34 (single model)
0.6
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#188model2_DenseNet121
0.6
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#189G_Mans_v1 (single model):
0.6
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#190haw-baseline (single model)
0.6
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#191DearBrave (single model)
0.4
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#192Multi-CNN (ensemble)
0.4
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#193inceptionv3_single_NN
0.4
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#194rayOfLightSingle (Single Model)
0.4
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#195Test model habbe
0.4
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#196HinaNet (single model)
0.4
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#197mwowra-conditional (single)
0.4
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#198multihead_model (one model for all pathologies)
0.4
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#199MLC9_Densenet (single model)
0.4
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#200Baseline
0.2
NUM RADS BELOW CURVE· 2019-11-04
pyannote.audio: neural building blocks for speaker diarization Code
#201singlehead_models (single model combined)
0.2
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#202mobilenet (single model)
0.2
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#203Grp12v2USup2OSamp (ensemble)
0.2
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#204Chest-x-ray classification using
0.2
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#205UMLS_CLIP (single model)
0
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#206CombinedTrainDenseNet121 (single model)
0
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#207Grp12BigCNN
0
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#208DNET121-single
0
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#20912ASLv2(single)
0
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#210DenseNet121 (single model)
0
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#21112ASLv1(single)
0
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#212rayOfLight (ensemble)
0
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#213BASELINE DenseNet121
0
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#214BME_Final_v2
0
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#215{densenet121}{single model
0
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#216autobot
0
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#217{MLC02_DenseNet121}
0
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#218efficiantB5 (single model)
0
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#219apalepu1
0
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#220Erdem (single)
0
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#221Adalab Standard (Single Model)
0
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#222Adalab Standard (single model)
0
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#223zeroshot_medclip_baseline (ensemble)
0
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