Vangala Govindakrishnan Saipradeep

This paper develops a deep learning model for mitotic figure detection that generalizes across diverse histological regions and tumor types, achieving an F1-score of 0.7769.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

MAGE accurately identifies microbial strains and quantifies their abundances using read mapping information without relying on strain-specific markers.