Optimizing Artificial Intelligence Thresholds for Mammographic Lesion Detection: A Retrospective Study on Diagnostic Performance and Radiologist–Artificial Intelligence Discordance

Optimizing Artificial Intelligence Thresholds for Mammographic Lesion Detection: A Retrospective Study on Diagnostic Performance and Radiologist–Artificial Intelligence Discordance

<b>Background/Objectives:</b> Artificial intelligence (AI)-based systems are increasingly being used to assist radiologists in detecting breast cancer on mammograms. However, applying fixed AI score thresholds across diverse lesion types may compromise diagnostic performance, especially...

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Bibliographic Details
Main Authors: Taesun Han, Hyesun Yun, Young Keun Sur, Heeboong Park
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Diagnostics
Subjects:
artificial intelligence
mammography
breast cancer
BI-RADS
diagnostic thresholds
dense breast
Online Access:https://www.mdpi.com/2075-4418/15/11/1368
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