Machine Learning for Chronic Disease Management - Focus on Precision Oncology
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Explore the cutting-edge applications of machine learning in chronic disease management, with a focus on precision oncology, in this 45-minute talk by Dr. Rahul Krishnan, Assistant Professor at the University of Toronto. Delve into recent advances in developing statistical models for clinical biomarkers in multiple myeloma patients and discover how deep learning is revolutionizing risk-stratification tools using histopathological data. Gain insights into the intersection of computer science and medicine as Dr. Krishnan, a CIFAR AI Chair at the Vector Institute, shares his expertise in probabilistic inference and applied machine learning for healthcare challenges such as disease progression modeling and risk stratification.
Syllabus
Machine Learning for Chronic Disease Management
Taught by
Toronto Machine Learning Series (TMLS)
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent