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Activity Number: 384 - Recent Statistical Advances in Diagnostic Medicine
Type: Invited
Date/Time: Wednesday, August 5, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #309467
Title: Statistical Inference on the Accuracy of Computer-Aided Diagnosis (CAD) Using Artificial Intelligence-Based Systems
Author(s): Xiao-Hua Zhou*
Companies: Peking University
Keywords: Artificial neural networks; Classification; Deep learning; Machine learning; Sensitivity; Specificity

In the digital age of medicine computer-aided diagnosis (CAD) is commonly used in the routine clinical work for the detection and diagnosis of various diseases in different imaging modalities, such as the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography. Methods based on Artificial neural networks (ANN), such as deep learning methods, are also commonly used to develop the computer algorithm for the CAD. In this talk,I will outline assessment methodologies and statistical issues for the performance of AI-based CAD systems. I will also discuss some new methodological development in assessing the performance of AI-based CAD systems.

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

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