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
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Predicting Patients’ Response to Immunotherapy from Tumor Histopathology and Blood: Computational Science in Immuno-oncologyJuly 08, 2025Data Jamboree: Enhancing Childhood Cancer Data Sharing and UtilitySeptember 29, 2025 - September 30, 2025NCI Office of Data Sharing’s Annual Data Sharing Symposium 2025: How Data Advances the Impact of Cancer ResearchSeptember 30, 2025 - October 01, 2025Childhood Cancer Data Initiative (CCDI) Symposium 2025October 06, 2025 - October 07, 2025