Benjamin Besse

SHERLOC is a deep learning model for survival analysis using longitudinal ctDNA data, showing improved discrimination and calibration over existing methods in non-small-cell lung cancer.

This study uses single-cell RNA sequencing to analyze metastatic urothelial carcinoma and identifies macrophage-driven resistance to PD-(L)1 blockade as a key mechanism.

This paper develops a method using circulating DNA fragment end motifs and machine learning to detect cancer with high accuracy across multiple cancer types.