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AI in spotting high-risk characteristics of medical imaging and molecular pathology
Author(s) -
Chong Zhang,
Jionghui Gu,
Yangyang Zhu,
Zheling Meng,
Tong Tong,
Dongyang Li,
Zhenyu Liu,
Yang Du,
Kun Wang,
Jie Tian
Publication year - 2021
Publication title -
precision clinical medicine
Language(s) - English
Resource type - Journals
eISSN - 2096-5303
pISSN - 2516-1571
DOI - 10.1093/pcmedi/pbab026
Subject(s) - medical imaging , molecular imaging , perspective (graphical) , medical physics , clinical diagnosis , pathology , computer science , medicine , artificial intelligence , biology , intensive care medicine , microbiology and biotechnology , in vivo
Medical imaging provides a comprehensive perspective and rich information for disease diagnosis. Combined with artificial intelligence technology, medical imaging can be further mined for detailed pathological information. Many studies have shown that the macroscopic imaging characteristics of tumors are closely related to microscopic gene, protein and molecular changes. In order to explore the function of artificial intelligence algorithms in in-depth analysis of medical imaging information, this paper reviews the articles published in recent years from three perspectives: medical imaging analysis method, clinical applications and the development of medical imaging in the direction of pathological molecular prediction. We believe that AI-aided medical imaging analysis will be extensively contributing to precise and efficient clinical decision.

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