Oded Rotem

DM4ISL improves in silico labeling of fluorescence images by reducing noise artifacts and providing uncertainty maps, outperforming existing methods across six organelles.

This paper introduces DISCOVER, a generative model that disentangles latent spaces to provide interpretable explanations for image-based classification models in in vitro fertilization.

The paper uses sibling embryo data from the same IVF cohort to improve machine learning prediction of embryo implantation outcomes.