A systematic pan-cancer study on deep learning-based prediction of multi-omic biomarkers from routine pathology images

A systematic pan-cancer study on deep learning-based prediction of multi-omic biomarkers from routine pathology images

Abstract Background The objective of this comprehensive pan-cancer study is to evaluate the potential of deep learning (DL) for molecular profiling of multi-omic biomarkers directly from hematoxylin and eosin (H&E)-stained whole slide images. Methods A total of 12,093 DL models predicting 4031 m...

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Bibliographic Details
Main Authors: Salim Arslan, Julian Schmidt, Cher Bass, Debapriya Mehrotra, Andre Geraldes, Shikha Singhal, Julius Hense, Xiusi Li, Pandu Raharja-Liu, Oscar Maiques, Jakob Nikolas Kather, Pahini Pandya
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-024-00471-5

Internet

https://doi.org/10.1038/s43856-024-00471-5

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