BioinformaticsbioRxivPreprint
Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders
Ziyuan Zhao, Zoltan Maliga, Emmanuel C. Ogbonna…·Peter Karl Sorger
This paper introduces a human-in-the-loop framework using AI foundation models and sparse autoencoders to interpret H&E histology images and integrate them with molecular spatial profiling.