Medical Image Classification on Radimagenet benchmark leaderboard · SOTA2 Research

Medical Image Classification on Radimagenet

78.92Lung AccuracyMTL-KD

Evaluation Results

Method	Links
MTL-KD2024.04		78.92	33.89	91.97	48.51	43.34	21.03	18.48	84.18	54.9	55.75
LoRKD2024.04		78.72	36.95	91.87	48.8	43.26	21.41	19.26	84.6	55.93	56.26
STL-KD2024.04		78	31.74	91.34	46.57	43.09	19.77	19.43	83.83	52.19	54.99
Aligned-MTL2024.04		77.74	36.38	91.76	48.41	43.28	21.26	18.37	84.54	54.86	55.79
MTL2024.04		77.16	37.45	91.73	46.47	42.72	20.85	18.17	84.67	55.16	55.81
STL2024.04		76.42	33.94	91.55	49.32	41.8	20.62	20.31	83.88	51.05	54.91
MoCo-MTL2024.04		76.28	45.56	86.26	45.58	43.97	18.74	17.41	84.33	52.71	55.7
KF2024.04		64.57	20.38	95.82	45.56	39.03	24.18	16.69	78.46	51.74	51.01
Foundation2024.04		36.22	46.52	74.05	40.09	31.32	17.79	12.95	77.3	32.33	43.74