How to learn with intentional mistakes: NoisyEnsembles to overcome poor tissue quality for deep learning in computational pathology

How to learn with intentional mistakes: NoisyEnsembles to overcome poor tissue quality for deep learning in computational pathology

There is a lot of recent interest in the field of computational pathology, as many algorithms are introduced to detect, for example, cancer lesions or molecular features. However, there is a large gap between artificial intelligence (AI) technology and practice, since only a small fraction of the ap...

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Bibliographic Details
Main Authors: Robin S. Mayer, Steffen Gretser, Lara E. Heckmann, Paul K. Ziegler, Britta Walter, Henning Reis, Katrin Bankov, Sven Becker, Jochen Triesch, Peter J. Wild, Nadine Flinner
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Medicine
Subjects:
ovarian cancer
tissue quality
quality control
deep learning
machine learning
computational pathology
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2022.959068/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2022.959068/full

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