Improving disease classification performance and explainability of deep learning models in radiology with heatmap generators

As deep learning is widely used in the radiology field, the explainability of Artificial Intelligence (AI) models is becoming increasingly essential to gain clinicians’ trust when using the models for diagnosis. In this research, three experiment sets were conducted with a U-Net architecture to impr...

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Bibliographic Details
Main Authors: Akino Watanabe, Sara Ketabi, Khashayar Namdar, Farzad Khalvati
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Radiology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fradi.2022.991683/full