Multi-Label Classification on CheXpert

Metric: AVERAGE AUC ON 14 LABEL (higher is better)

LeaderboardDataset

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Results

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#	Model↕	AVERAGE AUC ON 14 LABEL▼	Augmentations	Paper	Date↕	Code
1	CFT (ensemble) Macao Polytechnic University	0.933	No	-	-	Code
2	DeepAUC-v1	0.93	No	Large-scale Robust Deep AUC Maximization: A New ...	2020-12-06	Code
3	Hierarchical-Learning-V1 (ensemble)	0.93	No	Interpreting chest X-rays via CNNs that exploit ...	2019-11-15	Code
4	YWW(ensemble)	0.929	No	-	-	-
5	Conditional-Training-LSR	0.929	No	-	-	-
6	Hierarchical-Learning-V4 (ensemble)	0.929	No	Interpreting chest X-rays via CNNs that exploit ...	2019-11-15	Code
7	Conditional-Training-LSR-V1	0.929	No	-	-	-
8	Hierarchical-Learning-V0 (ensemble)	0.929	No	-	-	-
9	Multi-Stage-Learning-CNN-V3 (ensemble)	0.928	No	-	-	-
10	DeepCNNsGM(ensemble)	0.928	No	-	-	-
11	inisis	0.927	No	-	-	-
12	DeepCNNs(ensemble)	0.927	No	-	-	-
13	SenseXDR	0.927	No	-	-	-
14	ihil (ensemble)	0.927	No	-	-	-
15	JF aboy ensemble_V2 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng	0.926	No	-	-	-
16	DRNet (ensemble)	0.926	No	-	-	-
17	yw	0.926	No	-	-	-
18	Anatomy-XNet-V1	0.926	No	Anatomy-XNet: An Anatomy Aware Convolutional Neu...	2021-06-10	-
19	hoanganh_VB_ensemble3	0.925	No	-	-	-
20	alimebkovk	0.925	No	-	-	-
21	uest	0.924	No	-	-	-
22	Hoang_VB_ensemble31_v	0.924	No	-	-	-
23	tedtt	0.924	No	-	-	-
24	as-hust-v3	0.924	No	-	-	-
25	hoanganh_VB_VN	0.924	No	-	-	-
26	Hierarchical-CNN-Ensemble-V1 (ensemble)	0.924	No	-	-	-
27	DE_APR ensemble ltt	0.923	No	-	-	-
28	DE_APR_N ensemble ltt	0.923	No	-	-	-
29	Multi-Stage-Learning-CNN-V2 (ensemble)	0.923	No	-	-	-
30	Weighted-CNN(ensemble)	0.923	No	-	-	-
31	hoanganhcnu_ensemble27_v	0.923	No	-	-	-
32	YJ&&YWW :https://github.com/inisis/chexper	0.923	No	-	-	-
33	as-hust-v1	0.923	No	-	-	-
34	Maxium (ensemble)	0.923	No	-	-	-
35	as-hust-v2	0.922	No	-	-	-
36	Average-CNN(ensemble)	0.922	No	-	-	-
37	MaxAUC	0.922	No	-	-	-
38	zjr(ensembel)	0.921	No	-	-	-
39	SuperCNNv3	0.921	No	-	-	-
40	hyc	0.921	No	-	-	-
41	hoangnguyenkcv1	0.921	No	-	-	-
42	{"submit_id": "0x3c7b0af1b5784c159daf259c58543aa3", "predict_id": "0x67b23473183f4f43afa3b37edbc5d7fe", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	0.92	No	-	-	-
43	HOANG_VB_VN_2	0.92	No	-	-	-
44	BDNB	0.919	No	-	-	-
45	JF Coolver ensemble	0.919	No	-	-	-
46	thang ensemble colo	0.919	No	-	-	-
47	hoangnn9 ensemble VBV	0.919	No	-	-	-
48	JF aboy ensemble_V1 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng	0.919	No	-	-	-
49	{"submit_id": "0x33aeb0f2525e482a886196c273bdf1ba", "predict_id": "0xff2f60907da8440d98ff17f0af749535", "submitter_id": "0x0b382a226d4548c9b441f19b1907fe0f"	0.919	No	-	-	-
50	brian-baseline-v2	0.919	No	-	-	-
51	DE_JUN4_RS_EN ensemble LTT	0.918	No	-	-	-
52	Mehdi_You (ensemble)	0.918	No	-	-	-
53	A Good Model (single model) Macao Polytechnic University	0.918	No	-	-	Code
54	A Good Model (single model)	0.918	No	-	-	-
55	Anatomy-XNet (ensemble)	0.917	No	Anatomy-XNet: An Anatomy Aware Convolutional Neu...	2021-06-10	-
56	Ensemble_v2	0.917	No	-	-	-
57	Deep-CNNs-V1	0.917	No	-	-	-
58	vdn6 ensemble ltt	0.917	No	-	-	-
59	Overfit ensemble OTH-A	0.917	No	-	-	-
60	thangbk(ensemble)	0.917	No	-	-	-
61	desmond	0.916	No	-	-	-
62	DE_JUN1_RS_EN ensemble LTT	0.916	No	-	-	-
63	DE_JUN3_RS_EN ensemble LTT	0.916	No	-	-	-
64	{"submit_id": "0x57dc2989f0474ca095d0841df09cfb18", "predict_id": "0xd43bcf7d4c9b467894db2b274b18794e", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	0.916	No	-	-	-
65	ATT-AW-v1	0.916	No	-	-	-
66	{"submit_id": "0xeb9c9e79ed9e4410a2a37d62322f4585", "predict_id": "0x735b718280b14e83895decbc31641f87", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"	0.916	No	-	-	-
67	Multi-Stage-Learning-CNN-V0	0.916	No	-	-	-
68	TGNB	0.915	No	-	-	-
69	ensemble SN	0.915	No	-	-	-
70	zhangjingyan	0.915	No	-	-	-
71	Deadpoppy Ensemble	0.915	No	-	-	-
72	hoangnguyenkcv-ensemble28	0.915	No	-	-	-
73	DE_JUN2_RS_EN ensemble LTT	0.914	No	-	-	-
74	GRNB	0.914	No	-	-	-
75	Deep-CNNs (ensemble)	0.914	No	-	-	-
76	Sky-Model	0.913	No	-	-	-
77	JF Deadpoppy	0.913	No	-	-	-
78	YWW-YJ:https://github.com/inisis/chexper	0.913	No	-	-	-
79	zjy	0.912	No	-	-	-
80	WL_Baseline (ensemble)	0.912	No	-	-	-
81	KCV-CNN-ensemble-CN	0.911	No	-	-	-
82	songta	0.911	No	-	-	-
83	bhtrun	0.911	No	-	-	-
84	anatomy_xnet_v1 (single model)	0.911	No	-	-	-
85	DS_APR_N single model ltt	0.911	No	-	-	-
86	DS_APR single model LTT	0.911	No	-	-	-
87	brian-baseline	0.911	No	-	-	-
88	ensemble SNU	0.91	No	-	-	-
89	HinaNetV2 (ensemble)	0.909	No	-	-	-
90	KD-Prune10 (Single model)	0.909	No	-	-	-
91	G_Mans_ensembl	0.909	No	-	-	-
92	Masks and Manuscripts	0.909	No	Masks and Manuscripts: Advancing Medical Pre-tra...	2024-07-23	-
93	guran_ri	0.908	No	-	-	-
94	vdnnn (ensemble)	0.908	No	-	-	-
95	BAAZT	0.908	No	-	-	-
96	Stanford Baseline (ensemble)	0.907	No	CheXpert: A Large Chest Radiograph Dataset with ...	2019-01-21	Code
97	vbn (single model)	0.907	No	-	-	-
98	muti_base (ensemble)	0.907	No	-	-	-
99	Z_Ensemble_V	0.907	No	-	-	-
100	{ForwardModelEnsembleCorrected} (ensemble)	0.906	No	-	-	-
101	LBC-v2 (ensemble)	0.906	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
102	LBC-v2	0.906	No	-	-	-
103	LBC-v2 (ensemble)	0.906	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
104	Multi-CNN	0.905	No	-	-	-
105	hy	0.905	No	-	-	-
106	ForwardMECorrectedFull (ensemble)	0.905	No	-	-	-
107	JustAnotherDensenet	0.904	No	-	-	-
108	Orlando (single model)	0.903	No	-	-	-
109	Max (single model)	0.902	No	-	-	-
110	DeepLungsEnsemble	0.902	No	-	-	-
111	Ensemble_v1	0.901	No	-	-	-
112	Nakajima_ayas	0.901	No	-	-	-
113	MLC11 NotDense (single-model)	0.9	No	-	-	-
114	vn_2 single_model ltt	0.9	No	-	-	-
115	{AVG_MAX}(ensemble)	0.899	No	-	-	-
116	Z_Ensemble_	0.899	No	-	-	-
117	llllldz	0.899	No	-	-	-
118	DiseaseNet Samg2003 single model, UIUC, http://sambhavgupta.com	0.899	No	-	-	-
119	DiseaseNet Samg2003 single model, DPS RKP, http://sambhavgupta.co	0.899	No	-	-	-
120	LBC-v0	0.899	No	-	-	-
121	LBC-v0 (ensemble)	0.899	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
122	LBC-v0 (ensemble)	0.899	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
123	BUA	0.898	No	-	-	-
124	G_Mans_v2 (single model): LibAUC + coat_mini	0.898	No	-	-	-
125	ljc226	0.898	No	-	-	-
126	ForwardModelEnsemble (ensemble)	0.897	No	-	-	-
127	NewTrickTest (ensemble)	0.897	No	-	-	-
128	AccidentNet v1 (single model)	0.897	No	-	-	-
129	ylz-v01	0.896	No	-	-	-
130	ldz	0.896	No	-	-	-
131	Densenet	0.896	No	-	-	-
132	Stellarium-CheXpert-Local (single model)	0.896	No	-	-	-
133	Stellarium-CheXpert-Local	0.896	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
134	Stellarium-CheXpert-Local	0.896	No	Image Projective Transformation Rectification wi...	2022-10-12	Code
135	Deadpoppy Single	0.895	No	-	-	-
136	adoudo	0.895	No	-	-	-
137	{koala-large} (single model)	0.895	No	-	-	-
138	MVD121	0.895	No	-	-	-
139	hust(single model)	0.895	No	-	-	-
140	MM1	0.894	No	-	-	-
141	hycN	0.894	No	-	-	-
142	zhujier	0.894	No	-	-	-
143	U-Random-Ind (single)	0.894	No	-	-	-
144	HybridModelEnsemble (ensemble)	0.892	No	-	-	-
145	MVD121-320	0.891	No	-	-	-
146	ylz-v02	0.891	No	-	-	-
147	pause	0.89	No	-	-	-
148	Overfit ensemble OT	0.89	No	-	-	-
149	Haruka_Hamasak	0.89	No	-	-	-
150	DenseNet169 at 320x320 (single model)	0.889	No	-	-	-
151	LR-baseline (ensemble)	0.889	No	-	-	-
152	DataAugFTW (single model)	0.888	No	-	-	-
153	{koala} (single model)	0.888	No	-	-	-
154	Xception (single model)	0.887	No	-	-	-
155	Stellarium (single model)	0.887	No	-	-	-
156	Stellarium	0.887	No	-	-	-
157	pm_rn50_0.15pp	0.887	No	-	-	-
158	baseline3	0.886	No	-	-	-
159	PrateekMunja	0.886	No	-	-	-
160	MVR50	0.886	No	-	-	-
161	MNet-Fix (Single Model)	0.884	No	-	-	-
162	Coolver XH	0.884	No	-	-	-
163	Naive Densenet	0.883	No	-	-	-
164	mhealth_buet (single model)	0.883	No	-	-	-
165	Aoitori (single model)	0.882	No	-	-	-
166	{chexpert-classifier}(single model)	0.882	No	-	-	-
167	DearBrave (single model)	0.882	No	-	-	-
168	AccidentNet V2 (single model)	0.881	No	-	-	-
169	{densenet} (single model)	0.88	No	-	-	-
170	Yoake (single model)	0.879	No	-	-	-
171	MLC11 Baseline (single-model)	0.878	No	-	-	-
172	DenseNet	0.876	No	-	-	-
173	HCL1 (single model)	0.876	No	-	-	-
174	MLGCN (single model)	0.875	No	-	-	-
175	GCN_densenet121-single mode	0.875	No	-	-	-
176	GreenTeaCalpis (single model)	0.873	No	-	-	-
177	Multi-CNN (ensemble)	0.873	No	-	-	-
178	BASELINE ResNet50	0.871	No	-	-	-
179	baseline1 (single model)	0.868	No	-	-	-
180	Baseline DenseNet161	0.868	No	-	-	-
181	DSENet	0.865	No	-	-	-
182	Densenet-Basic Single NUS	0.863	No	-	-	-
183	KD_Mobilenet (single model)	0.862	No	-	-	-
184	{GoDense} (single model)	0.861	No	-	-	-
185	inceptionv3_single_NN	0.861	No	-	-	-
186	MLKD (Single model)	0.86	No	-	-	-
187	BASELINE Acorn	0.86	No	-	-	-
188	ErrorNet (single model)	0.859	No	-	-	-
189	SleepNet (single model)	0.859	No	-	-	-
190	baseline2	0.858	No	-	-	-
191	UMLS_CLIP (single model)	0.858	No	-	-	-
192	haw02 (single model)	0.854	No	-	-	-
193	CombinedTrainDenseNet121 (single model)	0.853	No	-	-	-
194	rayOfLightSingle (Single Model)	0.851	No	-	-	-
195	Model_Team_34 (single model)	0.85	No	-	-	-
196	Test model habbe	0.85	No	-	-	-
197	model2_DenseNet121	0.848	No	-	-	-
198	Baseline	0.848	No	-	-	-
199	HinaNet (single model)	0.844	No	-	-	-
200	singlehead_models (single model combined)	0.842	No	-	-	-
201	mwowra-conditional (single)	0.84	No	-	-	-
202	multihead_model (one model for all pathologies)	0.838	No	-	-	-
203	mobilenet (single model)	0.837	No	-	-	-
204	Grp12BigCNN	0.835	No	-	-	-
205	MLC9_Densenet (single model)	0.834	No	-	-	-
206	Grp12v2USup2OSamp (ensemble)	0.83	No	-	-	-
207	DNET121-single	0.822	No	-	-	-
208	DensNet121	0.805	No	CheXclusion: Fairness gaps in deep chest X-ray c...	2020-02-14	Code
209	G_Mans_v1 (single model):	0.797	No	-	-	-
210	12ASLv2(single)	0.769	No	-	-	-
211	DenseNet121 (single model)	0.76	No	-	-	-
212	12ASLv1(single)	0.736	No	-	-	-
213	haw-baseline (single model)	0.732	No	-	-	-
214	rayOfLight (ensemble)	0.727	No	-	-	-
215	BASELINE DenseNet121	0.724	No	-	-	-
216	Chest-x-ray classification using	0.618	No	-	-	-
217	BME_Final_v2	0.615	No	-	-	-
218	{densenet121}{single model	0.606	No	-	-	-
219	autobot	0.606	No	-	-	-
220	{MLC02_DenseNet121}	0.575	No	-	-	-
221	efficiantB5 (single model)	0.531	No	-	-	-
222	apalepu1	0.524	No	-	-	-
223	Erdem (single)	0.5	No	-	-	-
224	Adalab Standard (Single Model)	0.481	No	-	-	-
225	Adalab Standard (single model)	0.481	No	-	-	-
226	zeroshot_medclip_baseline (ensemble)	0.479	No	-	-	-

#1CFT (ensemble) Macao Polytechnic University
0.933
AVERAGE AUC ON 14 LABEL
No paperCode
#2DeepAUC-v1
0.93
AVERAGE AUC ON 14 LABEL· 2020-12-06
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification Code
#3Hierarchical-Learning-V1 (ensemble)SOTA
0.93
AVERAGE AUC ON 14 LABEL· 2019-11-15
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels Code
#4YWW(ensemble)
0.929
AVERAGE AUC ON 14 LABEL
No paper
#5Conditional-Training-LSR
0.929
AVERAGE AUC ON 14 LABEL
No paper
#6Hierarchical-Learning-V4 (ensemble)
0.929
AVERAGE AUC ON 14 LABEL· 2019-11-15
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels Code
#7Conditional-Training-LSR-V1
0.929
AVERAGE AUC ON 14 LABEL
No paper
#8Hierarchical-Learning-V0 (ensemble)
0.929
AVERAGE AUC ON 14 LABEL
No paper
#9Multi-Stage-Learning-CNN-V3 (ensemble)
0.928
AVERAGE AUC ON 14 LABEL
No paper
#10DeepCNNsGM(ensemble)
0.928
AVERAGE AUC ON 14 LABEL
No paper
#11inisis
0.927
AVERAGE AUC ON 14 LABEL
No paper
#12DeepCNNs(ensemble)
0.927
AVERAGE AUC ON 14 LABEL
No paper
#13SenseXDR
0.927
AVERAGE AUC ON 14 LABEL
No paper
#14ihil (ensemble)
0.927
AVERAGE AUC ON 14 LABEL
No paper
#15JF aboy ensemble_V2 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng
0.926
AVERAGE AUC ON 14 LABEL
No paper
#16DRNet (ensemble)
0.926
AVERAGE AUC ON 14 LABEL
No paper
#17yw
0.926
AVERAGE AUC ON 14 LABEL
No paper
#18Anatomy-XNet-V1
0.926
AVERAGE AUC ON 14 LABEL· 2021-06-10
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
#19hoanganh_VB_ensemble3
0.925
AVERAGE AUC ON 14 LABEL
No paper
#20alimebkovk
0.925
AVERAGE AUC ON 14 LABEL
No paper
#21uest
0.924
AVERAGE AUC ON 14 LABEL
No paper
#22Hoang_VB_ensemble31_v
0.924
AVERAGE AUC ON 14 LABEL
No paper
#23tedtt
0.924
AVERAGE AUC ON 14 LABEL
No paper
#24as-hust-v3
0.924
AVERAGE AUC ON 14 LABEL
No paper
#25hoanganh_VB_VN
0.924
AVERAGE AUC ON 14 LABEL
No paper
#26Hierarchical-CNN-Ensemble-V1 (ensemble)
0.924
AVERAGE AUC ON 14 LABEL
No paper
#27DE_APR ensemble ltt
0.923
AVERAGE AUC ON 14 LABEL
No paper
#28DE_APR_N ensemble ltt
0.923
AVERAGE AUC ON 14 LABEL
No paper
#29Multi-Stage-Learning-CNN-V2 (ensemble)
0.923
AVERAGE AUC ON 14 LABEL
No paper
#30Weighted-CNN(ensemble)
0.923
AVERAGE AUC ON 14 LABEL
No paper
#31hoanganhcnu_ensemble27_v
0.923
AVERAGE AUC ON 14 LABEL
No paper
#32YJ&&YWW :https://github.com/inisis/chexper
0.923
AVERAGE AUC ON 14 LABEL
No paper
#33as-hust-v1
0.923
AVERAGE AUC ON 14 LABEL
No paper
#34Maxium (ensemble)
0.923
AVERAGE AUC ON 14 LABEL
No paper
#35as-hust-v2
0.922
AVERAGE AUC ON 14 LABEL
No paper
#36Average-CNN(ensemble)
0.922
AVERAGE AUC ON 14 LABEL
No paper
#37MaxAUC
0.922
AVERAGE AUC ON 14 LABEL
No paper
#38zjr(ensembel)
0.921
AVERAGE AUC ON 14 LABEL
No paper
#39SuperCNNv3
0.921
AVERAGE AUC ON 14 LABEL
No paper
#40hyc
0.921
AVERAGE AUC ON 14 LABEL
No paper
#41hoangnguyenkcv1
0.921
AVERAGE AUC ON 14 LABEL
No paper
#42{"submit_id": "0x3c7b0af1b5784c159daf259c58543aa3", "predict_id": "0x67b23473183f4f43afa3b37edbc5d7fe", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
0.92
AVERAGE AUC ON 14 LABEL
No paper
#43HOANG_VB_VN_2
0.92
AVERAGE AUC ON 14 LABEL
No paper
#44BDNB
0.919
AVERAGE AUC ON 14 LABEL
No paper
#45JF Coolver ensemble
0.919
AVERAGE AUC ON 14 LABEL
No paper
#46thang ensemble colo
0.919
AVERAGE AUC ON 14 LABEL
No paper
#47hoangnn9 ensemble VBV
0.919
AVERAGE AUC ON 14 LABEL
No paper
#48JF aboy ensemble_V1 JF HEALTHCARE https://github.com/deadpoppy/CheXpert-Challeng
0.919
AVERAGE AUC ON 14 LABEL
No paper
#49{"submit_id": "0x33aeb0f2525e482a886196c273bdf1ba", "predict_id": "0xff2f60907da8440d98ff17f0af749535", "submitter_id": "0x0b382a226d4548c9b441f19b1907fe0f"
0.919
AVERAGE AUC ON 14 LABEL
No paper
#50brian-baseline-v2
0.919
AVERAGE AUC ON 14 LABEL
No paper
#51DE_JUN4_RS_EN ensemble LTT
0.918
AVERAGE AUC ON 14 LABEL
No paper
#52Mehdi_You (ensemble)
0.918
AVERAGE AUC ON 14 LABEL
No paper
#53A Good Model (single model) Macao Polytechnic University
0.918
AVERAGE AUC ON 14 LABEL
No paperCode
#54A Good Model (single model)
0.918
AVERAGE AUC ON 14 LABEL
No paper
#55Anatomy-XNet (ensemble)
0.917
AVERAGE AUC ON 14 LABEL· 2021-06-10
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
#56Ensemble_v2
0.917
AVERAGE AUC ON 14 LABEL
No paper
#57Deep-CNNs-V1
0.917
AVERAGE AUC ON 14 LABEL
No paper
#58vdn6 ensemble ltt
0.917
AVERAGE AUC ON 14 LABEL
No paper
#59Overfit ensemble OTH-A
0.917
AVERAGE AUC ON 14 LABEL
No paper
#60thangbk(ensemble)
0.917
AVERAGE AUC ON 14 LABEL
No paper
#61desmond
0.916
AVERAGE AUC ON 14 LABEL
No paper
#62DE_JUN1_RS_EN ensemble LTT
0.916
AVERAGE AUC ON 14 LABEL
No paper
#63DE_JUN3_RS_EN ensemble LTT
0.916
AVERAGE AUC ON 14 LABEL
No paper
#64{"submit_id": "0x57dc2989f0474ca095d0841df09cfb18", "predict_id": "0xd43bcf7d4c9b467894db2b274b18794e", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
0.916
AVERAGE AUC ON 14 LABEL
No paper
#65ATT-AW-v1
0.916
AVERAGE AUC ON 14 LABEL
No paper
#66{"submit_id": "0xeb9c9e79ed9e4410a2a37d62322f4585", "predict_id": "0x735b718280b14e83895decbc31641f87", "submitter_id": "0x30db016ad564455ba055eb7f7f4402ac"
0.916
AVERAGE AUC ON 14 LABEL
No paper
#67Multi-Stage-Learning-CNN-V0
0.916
AVERAGE AUC ON 14 LABEL
No paper
#68TGNB
0.915
AVERAGE AUC ON 14 LABEL
No paper
#69ensemble SN
0.915
AVERAGE AUC ON 14 LABEL
No paper
#70zhangjingyan
0.915
AVERAGE AUC ON 14 LABEL
No paper
#71Deadpoppy Ensemble
0.915
AVERAGE AUC ON 14 LABEL
No paper
#72hoangnguyenkcv-ensemble28
0.915
AVERAGE AUC ON 14 LABEL
No paper
#73DE_JUN2_RS_EN ensemble LTT
0.914
AVERAGE AUC ON 14 LABEL
No paper
#74GRNB
0.914
AVERAGE AUC ON 14 LABEL
No paper
#75Deep-CNNs (ensemble)
0.914
AVERAGE AUC ON 14 LABEL
No paper
#76Sky-Model
0.913
AVERAGE AUC ON 14 LABEL
No paper
#77JF Deadpoppy
0.913
AVERAGE AUC ON 14 LABEL
No paper
#78YWW-YJ:https://github.com/inisis/chexper
0.913
AVERAGE AUC ON 14 LABEL
No paper
#79zjy
0.912
AVERAGE AUC ON 14 LABEL
No paper
#80WL_Baseline (ensemble)
0.912
AVERAGE AUC ON 14 LABEL
No paper
#81KCV-CNN-ensemble-CN
0.911
AVERAGE AUC ON 14 LABEL
No paper
#82songta
0.911
AVERAGE AUC ON 14 LABEL
No paper
#83bhtrun
0.911
AVERAGE AUC ON 14 LABEL
No paper
#84anatomy_xnet_v1 (single model)
0.911
AVERAGE AUC ON 14 LABEL
No paper
#85DS_APR_N single model ltt
0.911
AVERAGE AUC ON 14 LABEL
No paper
#86DS_APR single model LTT
0.911
AVERAGE AUC ON 14 LABEL
No paper
#87brian-baseline
0.911
AVERAGE AUC ON 14 LABEL
No paper
#88ensemble SNU
0.91
AVERAGE AUC ON 14 LABEL
No paper
#89HinaNetV2 (ensemble)
0.909
AVERAGE AUC ON 14 LABEL
No paper
#90KD-Prune10 (Single model)
0.909
AVERAGE AUC ON 14 LABEL
No paper
#91G_Mans_ensembl
0.909
AVERAGE AUC ON 14 LABEL
No paper
#92Masks and Manuscripts
0.909
AVERAGE AUC ON 14 LABEL· 2024-07-23
Masks and Manuscripts: Advancing Medical Pre-training with End-to-End Masking and Narrative Structuring
#93guran_ri
0.908
AVERAGE AUC ON 14 LABEL
No paper
#94vdnnn (ensemble)
0.908
AVERAGE AUC ON 14 LABEL
No paper
#95BAAZT
0.908
AVERAGE AUC ON 14 LABEL
No paper
#96Stanford Baseline (ensemble)SOTA
0.907
AVERAGE AUC ON 14 LABEL· 2019-01-21
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Code
#97vbn (single model)
0.907
AVERAGE AUC ON 14 LABEL
No paper
#98muti_base (ensemble)
0.907
AVERAGE AUC ON 14 LABEL
No paper
#99Z_Ensemble_V
0.907
AVERAGE AUC ON 14 LABEL
No paper
#100{ForwardModelEnsembleCorrected} (ensemble)
0.906
AVERAGE AUC ON 14 LABEL
No paper
#101LBC-v2 (ensemble)
0.906
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#102LBC-v2
0.906
AVERAGE AUC ON 14 LABEL
No paper
#103LBC-v2 (ensemble)
0.906
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#104Multi-CNN
0.905
AVERAGE AUC ON 14 LABEL
No paper
#105hy
0.905
AVERAGE AUC ON 14 LABEL
No paper
#106ForwardMECorrectedFull (ensemble)
0.905
AVERAGE AUC ON 14 LABEL
No paper
#107JustAnotherDensenet
0.904
AVERAGE AUC ON 14 LABEL
No paper
#108Orlando (single model)
0.903
AVERAGE AUC ON 14 LABEL
No paper
#109Max (single model)
0.902
AVERAGE AUC ON 14 LABEL
No paper
#110DeepLungsEnsemble
0.902
AVERAGE AUC ON 14 LABEL
No paper
#111Ensemble_v1
0.901
AVERAGE AUC ON 14 LABEL
No paper
#112Nakajima_ayas
0.901
AVERAGE AUC ON 14 LABEL
No paper
#113MLC11 NotDense (single-model)
0.9
AVERAGE AUC ON 14 LABEL
No paper
#114vn_2 single_model ltt
0.9
AVERAGE AUC ON 14 LABEL
No paper
#115{AVG_MAX}(ensemble)
0.899
AVERAGE AUC ON 14 LABEL
No paper
#116Z_Ensemble_
0.899
AVERAGE AUC ON 14 LABEL
No paper
#117llllldz
0.899
AVERAGE AUC ON 14 LABEL
No paper
#118DiseaseNet Samg2003 single model, UIUC, http://sambhavgupta.com
0.899
AVERAGE AUC ON 14 LABEL
No paper
#119DiseaseNet Samg2003 single model, DPS RKP, http://sambhavgupta.co
0.899
AVERAGE AUC ON 14 LABEL
No paper
#120LBC-v0
0.899
AVERAGE AUC ON 14 LABEL
No paper
#121LBC-v0 (ensemble)
0.899
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#122LBC-v0 (ensemble)
0.899
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#123BUA
0.898
AVERAGE AUC ON 14 LABEL
No paper
#124G_Mans_v2 (single model): LibAUC + coat_mini
0.898
AVERAGE AUC ON 14 LABEL
No paper
#125ljc226
0.898
AVERAGE AUC ON 14 LABEL
No paper
#126ForwardModelEnsemble (ensemble)
0.897
AVERAGE AUC ON 14 LABEL
No paper
#127NewTrickTest (ensemble)
0.897
AVERAGE AUC ON 14 LABEL
No paper
#128AccidentNet v1 (single model)
0.897
AVERAGE AUC ON 14 LABEL
No paper
#129ylz-v01
0.896
AVERAGE AUC ON 14 LABEL
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#130ldz
0.896
AVERAGE AUC ON 14 LABEL
No paper
#131Densenet
0.896
AVERAGE AUC ON 14 LABEL
No paper
#132Stellarium-CheXpert-Local (single model)
0.896
AVERAGE AUC ON 14 LABEL
No paper
#133Stellarium-CheXpert-Local
0.896
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#134Stellarium-CheXpert-Local
0.896
AVERAGE AUC ON 14 LABEL· 2022-10-12
Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification Code
#135Deadpoppy Single
0.895
AVERAGE AUC ON 14 LABEL
No paper
#136adoudo
0.895
AVERAGE AUC ON 14 LABEL
No paper
#137{koala-large} (single model)
0.895
AVERAGE AUC ON 14 LABEL
No paper
#138MVD121
0.895
AVERAGE AUC ON 14 LABEL
No paper
#139hust(single model)
0.895
AVERAGE AUC ON 14 LABEL
No paper
#140MM1
0.894
AVERAGE AUC ON 14 LABEL
No paper
#141hycN
0.894
AVERAGE AUC ON 14 LABEL
No paper
#142zhujier
0.894
AVERAGE AUC ON 14 LABEL
No paper
#143U-Random-Ind (single)
0.894
AVERAGE AUC ON 14 LABEL
No paper
#144HybridModelEnsemble (ensemble)
0.892
AVERAGE AUC ON 14 LABEL
No paper
#145MVD121-320
0.891
AVERAGE AUC ON 14 LABEL
No paper
#146ylz-v02
0.891
AVERAGE AUC ON 14 LABEL
No paper
#147pause
0.89
AVERAGE AUC ON 14 LABEL
No paper
#148Overfit ensemble OT
0.89
AVERAGE AUC ON 14 LABEL
No paper
#149Haruka_Hamasak
0.89
AVERAGE AUC ON 14 LABEL
No paper
#150DenseNet169 at 320x320 (single model)
0.889
AVERAGE AUC ON 14 LABEL
No paper
#151LR-baseline (ensemble)
0.889
AVERAGE AUC ON 14 LABEL
No paper
#152DataAugFTW (single model)
0.888
AVERAGE AUC ON 14 LABEL
No paper
#153{koala} (single model)
0.888
AVERAGE AUC ON 14 LABEL
No paper
#154Xception (single model)
0.887
AVERAGE AUC ON 14 LABEL
No paper
#155Stellarium (single model)
0.887
AVERAGE AUC ON 14 LABEL
No paper
#156Stellarium
0.887
AVERAGE AUC ON 14 LABEL
No paper
#157pm_rn50_0.15pp
0.887
AVERAGE AUC ON 14 LABEL
No paper
#158baseline3
0.886
AVERAGE AUC ON 14 LABEL
No paper
#159PrateekMunja
0.886
AVERAGE AUC ON 14 LABEL
No paper
#160MVR50
0.886
AVERAGE AUC ON 14 LABEL
No paper
#161MNet-Fix (Single Model)
0.884
AVERAGE AUC ON 14 LABEL
No paper
#162Coolver XH
0.884
AVERAGE AUC ON 14 LABEL
No paper
#163Naive Densenet
0.883
AVERAGE AUC ON 14 LABEL
No paper
#164mhealth_buet (single model)
0.883
AVERAGE AUC ON 14 LABEL
No paper
#165Aoitori (single model)
0.882
AVERAGE AUC ON 14 LABEL
No paper
#166{chexpert-classifier}(single model)
0.882
AVERAGE AUC ON 14 LABEL
No paper
#167DearBrave (single model)
0.882
AVERAGE AUC ON 14 LABEL
No paper
#168AccidentNet V2 (single model)
0.881
AVERAGE AUC ON 14 LABEL
No paper
#169{densenet} (single model)
0.88
AVERAGE AUC ON 14 LABEL
No paper
#170Yoake (single model)
0.879
AVERAGE AUC ON 14 LABEL
No paper
#171MLC11 Baseline (single-model)
0.878
AVERAGE AUC ON 14 LABEL
No paper
#172DenseNet
0.876
AVERAGE AUC ON 14 LABEL
No paper
#173HCL1 (single model)
0.876
AVERAGE AUC ON 14 LABEL
No paper
#174MLGCN (single model)
0.875
AVERAGE AUC ON 14 LABEL
No paper
#175GCN_densenet121-single mode
0.875
AVERAGE AUC ON 14 LABEL
No paper
#176GreenTeaCalpis (single model)
0.873
AVERAGE AUC ON 14 LABEL
No paper
#177Multi-CNN (ensemble)
0.873
AVERAGE AUC ON 14 LABEL
No paper
#178BASELINE ResNet50
0.871
AVERAGE AUC ON 14 LABEL
No paper
#179baseline1 (single model)
0.868
AVERAGE AUC ON 14 LABEL
No paper
#180Baseline DenseNet161
0.868
AVERAGE AUC ON 14 LABEL
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#181DSENet
0.865
AVERAGE AUC ON 14 LABEL
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#182Densenet-Basic Single NUS
0.863
AVERAGE AUC ON 14 LABEL
No paper
#183KD_Mobilenet (single model)
0.862
AVERAGE AUC ON 14 LABEL
No paper
#184{GoDense} (single model)
0.861
AVERAGE AUC ON 14 LABEL
No paper
#185inceptionv3_single_NN
0.861
AVERAGE AUC ON 14 LABEL
No paper
#186MLKD (Single model)
0.86
AVERAGE AUC ON 14 LABEL
No paper
#187BASELINE Acorn
0.86
AVERAGE AUC ON 14 LABEL
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#188ErrorNet (single model)
0.859
AVERAGE AUC ON 14 LABEL
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#189SleepNet (single model)
0.859
AVERAGE AUC ON 14 LABEL
No paper
#190baseline2
0.858
AVERAGE AUC ON 14 LABEL
No paper
#191UMLS_CLIP (single model)
0.858
AVERAGE AUC ON 14 LABEL
No paper
#192haw02 (single model)
0.854
AVERAGE AUC ON 14 LABEL
No paper
#193CombinedTrainDenseNet121 (single model)
0.853
AVERAGE AUC ON 14 LABEL
No paper
#194rayOfLightSingle (Single Model)
0.851
AVERAGE AUC ON 14 LABEL
No paper
#195Model_Team_34 (single model)
0.85
AVERAGE AUC ON 14 LABEL
No paper
#196Test model habbe
0.85
AVERAGE AUC ON 14 LABEL
No paper
#197model2_DenseNet121
0.848
AVERAGE AUC ON 14 LABEL
No paper
#198Baseline
0.848
AVERAGE AUC ON 14 LABEL
No paper
#199HinaNet (single model)
0.844
AVERAGE AUC ON 14 LABEL
No paper
#200singlehead_models (single model combined)
0.842
AVERAGE AUC ON 14 LABEL
No paper
#201mwowra-conditional (single)
0.84
AVERAGE AUC ON 14 LABEL
No paper
#202multihead_model (one model for all pathologies)
0.838
AVERAGE AUC ON 14 LABEL
No paper
#203mobilenet (single model)
0.837
AVERAGE AUC ON 14 LABEL
No paper
#204Grp12BigCNN
0.835
AVERAGE AUC ON 14 LABEL
No paper
#205MLC9_Densenet (single model)
0.834
AVERAGE AUC ON 14 LABEL
No paper
#206Grp12v2USup2OSamp (ensemble)
0.83
AVERAGE AUC ON 14 LABEL
No paper
#207DNET121-single
0.822
AVERAGE AUC ON 14 LABEL
No paper
#208DensNet121
0.805
AVERAGE AUC ON 14 LABEL· 2020-02-14
CheXclusion: Fairness gaps in deep chest X-ray classifiers Code
#209G_Mans_v1 (single model):
0.797
AVERAGE AUC ON 14 LABEL
No paper
#21012ASLv2(single)
0.769
AVERAGE AUC ON 14 LABEL
No paper
#211DenseNet121 (single model)
0.76
AVERAGE AUC ON 14 LABEL
No paper
#21212ASLv1(single)
0.736
AVERAGE AUC ON 14 LABEL
No paper
#213haw-baseline (single model)
0.732
AVERAGE AUC ON 14 LABEL
No paper
#214rayOfLight (ensemble)
0.727
AVERAGE AUC ON 14 LABEL
No paper
#215BASELINE DenseNet121
0.724
AVERAGE AUC ON 14 LABEL
No paper
#216Chest-x-ray classification using
0.618
AVERAGE AUC ON 14 LABEL
No paper
#217BME_Final_v2
0.615
AVERAGE AUC ON 14 LABEL
No paper
#218{densenet121}{single model
0.606
AVERAGE AUC ON 14 LABEL
No paper
#219autobot
0.606
AVERAGE AUC ON 14 LABEL
No paper
#220{MLC02_DenseNet121}
0.575
AVERAGE AUC ON 14 LABEL
No paper
#221efficiantB5 (single model)
0.531
AVERAGE AUC ON 14 LABEL
No paper
#222apalepu1
0.524
AVERAGE AUC ON 14 LABEL
No paper
#223Erdem (single)
0.5
AVERAGE AUC ON 14 LABEL
No paper
#224Adalab Standard (Single Model)
0.481
AVERAGE AUC ON 14 LABEL
No paper
#225Adalab Standard (single model)
0.481
AVERAGE AUC ON 14 LABEL
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#226zeroshot_medclip_baseline (ensemble)
0.479
AVERAGE AUC ON 14 LABEL
No paper