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Computer Vision to Phenotype Human Diseases Across Physical and Molecular Scales

Offered By: Paul G. Allen School via YouTube

Tags

Computer Vision Courses Artificial Intelligence Courses Machine Learning Courses Histology Courses Medical Imaging Courses Biomedical Research Courses Spatial Transcriptomics Courses

Course Description

Overview

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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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