Computer Vision to Deeply Phenotype Human Diseases Across Physiological, Tissue, and Molecular Scales
Computer vision (CV) uses machines to understand and analyze images. When coupled with machine learning (ML), this technology has broad implications for the field of cancer research. In this webinar, Dr. James Zou will present new CV algorithms and describe how these can help identify the morphologies and phenotypes associated with complex diseases, such as cancer. He will discuss the general principles behind this technology as well as current ML tools, such as Ghorbani, NeurIPS 2020, Abid, and Nature MI 2020.
Dr. James Zou is an assistant professor of biomedical data science at Stanford University, as well as a Chan-Zuckerberg investigator and the faculty director of Stanford’s Artificial Intelligence for Health program.
Upcoming Events
- Social Determinants of Health with Large/Moderate Language Models on EHR Data: AI in Immuno-oncologyJuly 30, 2024CCDI Federated Data: Enhancing Data DiscoverabilityAugust 13, 2024Leveraging High-Performance Computing Resources and Using QIIME 2 to Advance Your Microbiome ProjectsAugust 27, 2024 - August 29, 2024NCI Office of Data Sharing’s Annual Data Sharing Symposium: Driving Cancer Advances Through Impactful ResearchOctober 16, 2024The Cancer Research Data Commons 2024 Fall Symposium: Ten Years of Empowering Cancer ResearchersOctober 16, 2024 - October 17, 2024