Federated learning for computational pathology on gigapixel whole slide images

Ming Y. Lu, Richard J. Chen, Dehan Kong, Jana Lipková, Rajendra Singh, Drew F. K. Williamson, Tiffany Y. Chen, Faisal Mahmood

Abstract: Highlights•We present the first large-scale application of privacy-preserving federated learning to weakly supervised computational pathology on gigapixel whole slide images.•Validation on multi-class classification, binary classification and survival prediction using multi-institutional datasets on two different disease models using thousands of gigapixel whole slide images.•Multiple instance learning-inspired framework for interpretable, weakly-supervised survival prediction from histology whole slides using patient-level labels from multiˇcentric data.