Artificial intelligence in anatomical pathology: building a strong foundation for precision medicine

被引:14
|
作者
Meroueh, Chady [1 ]
Chen, Zongming Eric [1 ,2 ]
机构
[1] Mayo Clin, Dept Lab Med & Pathol, Div Anat Pathol, Rochester, MN 55905 USA
[2] Mayo Clin, Dept Lab Med & Pathol, Div Anat Pathol, 200 First St SW, Rochester, MN 55905 USA
关键词
Artificial intelligence; Digital pathology; Quantitative image anal-ysis; Whole slide imaging; Machine learning; Deep learning; Convolution neural network; MYCOBACTERIUM-TUBERCULOSIS; RECURRENCE SCORE; CLASSIFICATION; IMMUNE; IMAGES;
D O I
10.1016/j.humpath.2022.07.008
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
With the convergence of digital pathology (DP) and artificial intelligence (AI), anatomic pa-thology practice has been experiencing an exciting paradigm shifting. Pathologists will be provided with an augmented ability to improve diagnostic accuracy, efficiency, and consistency. There will be subvisual morphometric features discovered and multiomics data integrated to provide better prog-nostic and theragnostic information to guide individual patients' management. The perspective for future precision medicine is promising. However, there are many challenges before AI-assisted DP diagnostic workflows can be successfully implemented. Herein, we briefly review some examples of AI application in anatomic pathology with an emphasis on the subspecialty of gastrointestinal pathol-ogy and discuss potential challenges for clinical implementation.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:31 / 38
页数:8
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