Agentic AI Framework for comprehensive medical imaging interpretation enabling lab intelligence скачать в хорошем качестве

Agentic AI Framework for comprehensive medical imaging interpretation enabling lab intelligence

Dr. Huang is an Assistant Professor of Pathology and Laboratory Medicine, with a secondary appointment in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania Perelman School of Medicine. After receiving a PhD in Electrical and Computer Engineering from Purdue University in August 2021, he completed a postdoctoral training at Stanford University from 2021 to 2024. Dr. Huang’s research focuses on advancing AI and machine learning in medicine, including the development of vision-language foundation models for pathology (featured on the cover of Nature Medicine 2023), pathologists-AI collaboration (Nature Biomedical Engineering 2024), neurodegenerative disease research (Nature Communications 2023), as well as work on optimizing large language models (Nature 2025). His work has been covered by The New York Times, Stanford Magazine, and Stanford Scope.