Applying Digital Twins to Unleash ML&AI for Solving Biomedical Challenges

As machine learning and artificial intelligence (ML&AI) show great promise in addressing biomedical challenges, their current application remains just the tip of the iceberg, constrained by unique challenges inherent to biomedical systems. In this talk, I propose a hypothesis: realistic digital twins could effectively address many of these challenges and unlock the full potential of ML&AI. I hope this discussion sparks an open dialogue on integrating ML&AI with mechanistic modeling and digital twin development, and exploring strategies to best assist patients in need. Find out more at: https://link.springer.com/article/10.1007/s10928-021-09798-1 *Contents* 00:00 - Applying Digital Twins to Unleash ML&AI for Solving Biomedical Challenges 33:38 - Questions and Discussions Moderator: James Sluka, PhD, Indiana University, Bloomington If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://youtube.com/playlist?list=PLiEtieOeWbMKh9VcQoinSwODcSZKMTGat Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/