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Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology

Authors :
Oliver Lester Saldanha
Chiara M. L. Loeffler
Jan Moritz Niehues
Marko van Treeck
Tobias P. Seraphin
Katherine Jane Hewitt
Didem Cifci
Gregory Patrick Veldhuizen
Siddhi Ramesh
Alexander T. Pearson
Jakob Nikolas Kather
Source :
npj Precision Oncology, Vol 7, Iss 1, Pp 1-5 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep learning can predict genetic alterations from pathology slides, but it is unclear how well these predictions generalize to external datasets. We performed a systematic study on Deep-Learning-based prediction of genetic alterations from histology, using two large datasets of multiple tumor types. We show that an analysis pipeline that integrates self-supervised feature extraction and attention-based multiple instance learning achieves a robust predictability and generalizability.

Details

Language :
English
ISSN :
2397768X
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
npj Precision Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.4f10e94592cb43cab9a2a2ce9a50b0d9
Document Type :
article
Full Text :
https://doi.org/10.1038/s41698-023-00365-0