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AI in Cancer Research and Diagnostics - IPAM at UCLA

Institute for Pure & Applied Mathematics (IPAM) via YouTube

Overview

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Explore the impact of artificial intelligence on cancer research and diagnostics in this 33-minute lecture by Frederick Klauschen from Ludwig-Maximilians-Universität München. Delve into the current state of AI in pathology, focusing on explainability methods and their applications in histological imaging. Discover how AI facilitates the analysis and interpretation of molecular "omics" data, and learn about the potential for integrating heterogeneous multi-modal data in both research and diagnostics. Examine topics such as anomaly detection, blackbox challenges, molecular profiling, image and molecular analysis, DNA methylation profiling, and clustering. Gain insights into whether AI will serve as an assist system for pathologists or potentially revolutionize the field with novel biomarkers and expert-level capabilities.

Syllabus

AI in pathology
Anomaly detection
Blackbox challenge
Molecular profiling
Image analysis
Molecular analysis
Challenges
Diagnostics
DNA Methylation Profiling
DNA Methylation Clustering
Outro

Taught by

Institute for Pure & Applied Mathematics (IPAM)

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