Deep learning has enabled great advances to be made in cancer research with regards to diagnosis, prognosis, and treatment. The study by Wang and colleagues in this issue of Cancer Research develops a deep learning algorithm with the ability to digitally stain histologic images, achieving reliable nuclei segmentation and cell classification. They use this tool to study the tumor morphologic microenvironment in tissue pathology images of patients with lung adenocarcinoma. On the basis of the image features, they develop a prognostic model and find correlations with the transcriptional activities of biological pathways.See related article by Wang et al., p. 2056.
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