Artificial Intelligence and Molecular Pathology: An Introduction to Principles, Techniques and Applications

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Artificial Intelligence and Molecular Pathology: An Introduction to Principles, Techniques and Applications

Continuing Education Credit is no longer available for this course. 
Description:

This lecture will cover the history, principles, and techniques of artificial intelligence (AI) systems with a focus on practical applications in molecular pathology.  The lecture will emphasize the high-level principles, strengths, and weaknesses of the various methods while also providing a window into the mathematical foundations.  Popular machine learning techniques ranging from traditional (e.g., linear models, clustering, decision trees) to state-of-the-art deep neural networks (large language models, convolutional networks) will be covered.  AI's effect on the future of molecular pathology will be speculated with the audience's encouraged participation.


Learning Objectives:
    1. Explain what AI systems can accomplish in the field of molecular pathology.
    2. Explain the principles and capabilities of AI systems.
    3. Understand how to apply the principles and techniques of machine learning to construct predictive models, with a focus on supervised and unsupervised learning approaches.
    4. Explain the various ways that AI systems have been used in molecular pathology to-date and how state-of-the-art techniques may be used to improve current laboratory processes in the future.




Speaker:

Jamal Benhamida, MD
Memorial Sloan Kettering Cancer Center

 Moderator:

Thomas Lee, MD, PhD
UCLA David Geffen School of Medicine

Duration: 1 Hour
Level of Instruction: Intermediate
Date Recorded: July 18 , 2023

How to Register:

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  3. Click "Complete Registration" button - you will receive a Zoom calendar invite

Continuing Education Credit Information

Continuing Education Credit is no longer available for this course. 
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