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Activity Number: 378 - Study Design and Statistical Challenges for AI/ML Based Medical Tests
Type: Topic-Contributed
Date/Time: Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #317601
Title: Statistical Challenges in the Design and Validation of Medical Deep Learning Models
Author(s): Andrew Beam*
Companies: Harvard
Keywords: deep learning; medical imaging ; artificial intelligence
Abstract:

Diagnostic medical imaging has been transformed in recent years by deep learning models trained on large amounts of patient data. Though there has been much progress and enthusiasm, these approaches have shed new light on classic issues in confounding, study design, and model validation. In this talk, we will highlight key challenges in the deep learning model validation pipeline and provide examples of subtle ways that these challenges may present themselves at different stages of model development.


Authors who are presenting talks have a * after their name.

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