Prognostic Significance of Immune Cell Populations Identified by Machine Learning in Colorectal Cancer Using Routine Hematoxylin and Eosin-Stained Sections.

Juha P VäyrynenMai Chan LauKoichiro HarukiAndressa Dias CostaJennifer BorowskyMelissa ZhaoKenji FujiyoshiKota ArimaTyler S TwomblyJunko KishikawaSimeng Gu Saina Aminmozaffari Shan-Shan ShiYoshifumi BabaNaohiko AkimotoTomotaka UgaiAnnacarolina F L Da SilvaMingyang SongKana WuAndrew T ChanReiko NishiharaCharles S FuchsJeffrey A MeyerhardtMarios GiannakisShuji OginoJonathan A Nowak

Published in: Clinical cancer research : an official journal of the American Association for Cancer Research (2020)

These findings highlight the potential for machine learning assessment of H&E-stained sections to provide robust, quantitative tumor-immune biomarkers for precision medicine.

Keyphrases

machine learning
artificial intelligence
big data
clinical practice
deep learning
high resolution
human health
risk assessment
genetic diversity
clinical evaluation