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

Seung-Yeon YooHye Eun ParkJung Ho KimXianyu WenSeorin JeongNam-Yun ChoHwang Gwan GwonHye Seung LeeSeung-Yong JeongSae-Won HanJeong Mo BaeGyeong 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