Improving generalization of deep learning models for diagnostic pathology by increasing variability in training data: Experiments on osteosarcoma subtypes
Background: Artificial intelligence has an emerging progress in diagnostic pathology. A large number of studies of applying deep learning models to histopathological images have been published in recent years. While many studies claim high accuracies, they may fall into the pitfalls of overfitting a...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2021-01-01
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Series: | Journal of Pathology Informatics |
Subjects: | |
Online Access: | http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2021;volume=12;issue=1;spage=30;epage=30;aulast=Tang |