Scientists at the Icahn School of Medicine at Mount Sinai have introduced a groundbreaking artificial intelligence tool, V2P (Variant to Phenotype), that identifies disease-causing genetic mutations and predicts associated diseases. Published in Nature Communications, this innovative method enhances genetic diagnostics for rare and complex diseases through advanced machine learning techniques. Unlike existing tools that only assess mutation harm, V2P connects genetic variants to specific phenotypic outcomes, streamlining patient diagnosis. First author David Stein highlights its potential to improve genetic interpretation accuracy and speed. Additionally, V2P aids researchers in identifying critical genes and pathways for drug development, facilitating precision medicine by tailoring therapies to individual genetic profiles. The tool currently categorizes mutations broadly and aims for future enhancements to predict precise disease outcomes. Backed by NIH funding, V2P represents a significant advancement toward personalized health care, promising to transform research and clinical practice. Explore more AI innovations at Mount Sinai: Mount Sinai AI.
