Deep learning predicts chromosomal instability from histopathology images.
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ABSTRACT:
SUBMITTER: Xu Z
PROVIDER: S-EPMC8099498 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
Deep learning predicts chromosomal instability from histopathology images.
Xu Zhuoran Z Verma Akanksha A Naveed Uska U Bakhoum Samuel F SF Khosravi Pegah P Elemento Olivier O
iScience 20210403 5
Chromosomal instability (CIN) is a hallmark of human cancer yet not readily testable for patients with cancer in routine clinical setting. In this study, we sought to explore whether CIN status can be predicted using ubiquitously available hematoxylin and eosin histology through a deep learning-based model. When applied to a cohort of 1,010 patients with breast cancer (Training set: n = 858, Test set: n = 152) from The Cancer Genome Atlas where 485 patients have high CIN status, our model accura ...[more]
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