Key Patches Are All You Need: A Multiple Instance Learning Framework For Robust Medical Diagnosis

arXiv:2405.01654v1 Announce Type: new
Abstract: Deep learning models have revolutionized the field of medical image analysis, due to their outstanding performances. However, they are sensitive to spurious correlations, often taking advantage of dataset bias to improve results for in-domain data, but jeopardizing their generalization capabilities. In this paper, we propose to limit the amount of information these models use to reach the final classification, by using a multiple instance learning (MIL) framework. MIL forces the model to use only a …

arxiv cs.cv diagnosis framework instance key medical multiple robust type