Applied Machine Learning in Healthcare - Practical and Legal Considerations
Toronto Machine Learning Series (TMLS) via YouTube
Overview
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Explore the transformative potential and challenges of applied machine learning in healthcare through this 29-minute conference talk from the Toronto Machine Learning Series. Gain insights from experts Mary Jane Dykeman, Partner & Co-Founder of INQ Data Law, and Muhammad Mamdani, Vice President of Data Science and Advanced Analytics at Unity Health Toronto. Discover how machine learning can revolutionize healthcare through automation, prediction, and optimization. Delve into the complexities surrounding data acquisition, storage, and utilization, as well as the development of practical machine learning algorithms. Examine the crucial legal and ethical considerations for data access and application in healthcare. Learn about change management principles essential for successful implementation of ML in medical settings. Acquire a comprehensive understanding of the process of applying machine learning to healthcare, balancing its immense potential with necessary legal and ethical safeguards.
Syllabus
Applied Machine Learning in Healthcare - Practical and Legal Considerations
Taught by
Toronto Machine Learning Series (TMLS)