Kevin Michael Boehm

This paper develops a multimodal transformer model using H&E images and text reports to predict recurrence scores in hormone receptor-positive breast cancer, achieving high accuracy and generalizability.

The paper trains a random forest classifier, ForestMHC, to predict MHC-I peptide presentation using a million human peptides, outperforming existing tools on test sets and mass spectrometry data.