卫生专业人员
深度学习
人工智能
污渍
癌症
病理
分割
计算机科学
医学
医学物理学
心理学
医疗保健
内科学
染色
经济增长
经济
作者
Carlos Rodríguez‐Antolín
出处
期刊:Cancer Research
[American Association for Cancer Research]
日期:2020-05-15
卷期号:80 (10): 1912-1913
被引量:1
标识
DOI:10.1158/0008-5472.can-20-0647
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI