Computer Vision to Phenotype Human Diseases Across Physical and Molecular Scales
Offered By: Paul G. Allen School via YouTube
Course Description
Overview
Explore cutting-edge computer vision algorithms for learning complex morphologies and phenotypes crucial to human diseases in this research seminar. Delve into examples spanning physical scales from macro to micro, including video-based AI for heart function assessment, spatial transcriptomics generation from histology images, and immune cell morphodynamics learning. Discover new design principles and tools for human-compatible and robust AI that enable these technologies. Gain insights from James Zou, an assistant professor at Stanford University and Chan-Zuckerberg investigator, as he discusses his work in developing novel machine learning algorithms to study human health and diseases, as well as making ML more reliable, accountable, and human-compatible.
Syllabus
Computer Vision to Phenotype Human Diseases Across Phys. and Molecular Scales (James Zou, Stanford)
Taught by
Paul G. Allen School
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