Alexandros Sigaras

EXaCT-2 is a whole exome sequencing platform that detects various cancer-related genomic features with high accuracy and sensitivity, outperforming standard assays in detecting sub-clonal mutations and molecular metrics.

This paper develops BELA, a deep learning model for ploidy prediction in human blastocysts using time-lapse imaging, achieving an AUC of 0.76 on the Weill Cornell dataset.

This paper introduces a weakly-supervised method to predict tumor purity from H&E stained slides, achieving high accuracy and enabling clinical applications.