医学
数字化病理学
H&E染色
人工智能
深度学习
病理
光学(聚焦)
数据科学
生物信息学
计算机科学
染色
物理
光学
生物
作者
Kelsey E. McHugh,Rish K. Pai
标识
DOI:10.1016/j.path.2023.05.003
摘要
The rapidly evolving development of artificial intelligence (AI) has spurred the development of numerous algorithms that augment information obtained from routine pathologic review of hematoxylin and eosin-stained slides. AI tools that predict prognosis and underlying molecular alterations have been the focus of much of the research to date. The results of these studies highlight the tremendous potential of AI to enhance our pathology reports by providing rapid predictions of key features that influence therapy and outcomes.
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