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MedFMC: A Real-world Dataset and Benchmark for Foundation Model Adaptation in Medical Image Classification

MedFMC, our novel dataset of 22,349 images from diverse clinical tasks, aims to bolster the use of pre-trained foundation models in medical image classification—a sector facing data scarcity. The application of MedFMC underscores the potential of these models and highlights the effectiveness of various baseline methods in terms of accuracy and cost-efficiency.

Dequan Wang, Xiaosong Wang, Lilong Wang, Mengzhang Li, Qian Da, Xiaoqiang Liu, Xiangyu Gao, Jun Shen, Junjun He, Tian Shen, Qi Duan, Jie Zhao, Kang Li, Yu Qiao, Shaoting Zhang