Ce qui reste vrai en recherche médicale | Debashis Sahoo | TEDxSanDiegoSalon

Debashis Sahoo examine comment des schémas stables en biologie pourraient rendre la recherche scientifique plus reproductible. Il explique comment l'intelligence artificielle peut aider à repérer des schémas biologiques invariants au sein de la complexité du corps humain. Selon lui, ces découvertes pourraient mettre en lumière des règles favorisant une médecine plus précise et un savoir scientifique plus fiable. L'intervention a été donnée lors d'un événement TEDxSanDiegoSalon.

• Méthodes d'IA pour repérer des schémas biologiques invariants
• Lien entre schémas stables et science reproductible
• Implications pour une médecine de précision

What if the key to making science more reproducible is hiding in the patterns that never change? In this talk, Debashis Sahoo explores how AI can help us uncover invariant biological patterns hidden within the enormous complexity of human biology—and how these discoveries could reveal the laws that make science more reliable, medicine more precise, and knowledge more trustworthy. Website: https://sites.google.com/view/debashis-sahoo Twitter/X: @sahoo00 LinkedIn: https://www.linkedin.com/in/sahoodebashis/ Facebook: https://www.facebook.com/debashis.sahoo #ReproducibleScience #AIinBiology #FutureOfMedicine #TEDxSanDiego #TEDx #MooresCancerCenter #Bioinformatics #Boolean Analysis #UCSD #AI Debashis Sahoo is a joint Associate Professor of Computer Science and Engineering and Pediatrics at the University of California, San Diego. He earned his B.Tech. from the Indian Institute of Technology, Kharagpur, and his M.S. and Ph.D. from Stanford University. His research bridges artificial intelligence and biology, developing logical and AI-driven methods to uncover invariant biological rules and predict patient responses. His work has led to advances in cancer and translational research, including the identification of CDX2 as a predictive biomarker in colon cancer (NEJM 2016). He is passionate about working at the intersection of disciplines and fostering collaborations among computational scientists, clinicians, and biologists to address real-world translational challenges. His group focuses on translating AI and logical modeling approaches into clinically actionable diagnostics and therapeutics. https://sites.google.com/view/debashis-sahoo This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx