Can Machine Learning Be Better than Biased Readers?

<b>Background:</b> Training machine learning (ML) models in medical imaging requires large amounts of labeled data. To minimize labeling workload, it is common to divide training data among multiple readers for separate annotation without consensus and then combine the labeled data for t...

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Bibliographic Details
Main Authors: Atsuhiro Hibi, Rui Zhu, Pascal N. Tyrrell
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Tomography
Subjects:
Online Access:https://www.mdpi.com/2379-139X/9/3/74