医学
工作流程
病理
癌症
胃肠病理学
内科学
胃肠道癌
生物信息学
结直肠癌
计算机科学
数据库
生物
作者
Jakob Nikolas Kather,Julien Caldéraro
标识
DOI:10.1038/s41575-020-0343-3
摘要
Deep learning can mine clinically useful information from histology. In gastrointestinal and liver cancer, such algorithms can predict survival and molecular alterations. Once pathology workflows are widely digitized, these methods could be used as inexpensive biomarkers. However, clinical translation requires training interdisciplinary researchers in both programming and clinical applications.
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