医学研究で変わらない真実を見つける | Debashis Sahoo | TEDxSanDiegoSalon

再現性の研究は、生物学に見られる安定したパターンが科学的知見をより信頼できるものにできるかを問います。TEDxSanDiegoSalonでのこの講演で、カリフォルニア大学サンディエゴ校の准教授Debashis Sahoo氏は、人間生物学の複雑さの中から不変の生物学的パターンを見つけるためにAIを用いる取り組みを紹介しています。氏は、そうしたパターンが、医療をより精密にし、科学的知識をより信頼できるものにする法則につながりうるという考えを示しています。

• AIを使って人間生物学の中の不変パターンを特定する
• 安定したパターンがより再現性の高い科学を支えうる理由
• より精密な医療と橋渡し研究への可能性

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