Whole-Slide Image Analysis Reveals Quantitative Landscape of Tumor-Immune Microenvironment in Colorectal Cancers.

Seung-Yeon Yoo Hye Eun Park Jung Ho KimXianyu WenSeorin JeongNam-Yun ChoHwang Gwan GwonHye Seung Lee Seung-Yong Jeong Sae-Won Han Jeong Mo Bae Gyeong Hoon Kang

Published in: Clinical cancer research : an official journal of the American Association for Cancer Research (2019)

Machine-learning-based image analysis can be useful for extracting quantitative information about the TIME, using whole-slide histopathologic images. This information can classify colorectal cancers into clinicopathologically relevant subgroups without performing a molecular analysis of the tumors.

Keyphrases

deep learning
machine learning
high resolution
health information
stem cells
artificial intelligence
convolutional neural network
single cell
healthcare
big data
social media