Ahmed Metwally
Senior Research Scientist, Google

AI in Healthcare

June 6, 4:30pm
Location: Santa Clara I

Precision Diabetes Prevention via Wearables and Artificial Intelligence

Type 2 diabetes (T2D) and prediabetes are classically defined by the level of glycemia. This classification does not take into account the heterogeneity in the pathophysiology of glucose dysregulation, the identification of which could inform targeted approaches to diabetes treatment and prevention. The four main metabolic subphenotypes are muscle insulin resistance, beta-cell dysfunction, incretin defect, and hepatic insulin resistance. They present to varying degrees in individuals predisposed to T2D. This presentation will delve into the utilization of glucose time-series analysis for the prediction of metabolic subphenotypes, and how this technology can be implemented to benefit millions of people globally through the use of wearable devices. Additionally, it will explore the framework’s applications in the study of COVID-19-induced new-onset diabetes.

Dr. Ahmed Metwally is a senior research scientist at Google. His research focuses on developing AI methods for longitudinal multimodal biomedical data fusion (wearables and omics) to detect cardiometabolic and infectious diseases early and personalize their treatments. Previously, he was a senior AI scientist at Illumina. Ahmed was a postdoctoral scholar in the Snyder lab at Stanford University (2018-2021). Ahmed holds a PhD in Biomedical Engineering and an MS in Computer Science, both from the University of Illinois at Chicago (2018). He received B.Sc. in Biomedical Engineering from Cairo University, Egypt. He has over 50 publications in prestigious journals, and is a co-inventor of two patents relating to diabetes prevention. Ahmed also led the Stanford Wearable Electronics Initiative and co-led the Stanford initiative for early prediction of COVID-19 using smartwatches. He is an IEEE senior member, and he was elected globally to serve on the board of IEEE EMBS from 2017 to 2019. He has received numerous awards, including the NIH Predoctoral Translational Scientist fellowship, Stanford RISE award, and ISMB’20 best talk award.