Potentials of AI in medical image analysis in Gastroenterology and Hepatology

被引：29

作者：

Chen, Hao ^{[1
]}

Sung, Joseph J. Y. ^{[2
]}

机构：

[1] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R China

[2] Chinese Univ Hong Kong, Dept Med & Therapeut, Shatin, Hong Kong, Peoples R China

来源：

JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY | 2021年 / 36卷 / 01期

关键词：

artificial intelligence (AI); deep learning (DL); endoscopy; gastroenterology; hepatology; machine learning (ML); pathology; radiology; POLYPS;

D O I：

10.1111/jgh.15327

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

With the advancement of artificial intelligence (AI) technology, it comes in a big wave carrying possibly huge impact in the field of medicine. Gastroenterology and hepatology, being a specialty relying much on diagnostic imaging, endoscopy, and histopathology, AI technology has promised improving the quality and consistency of care to the patients. In this review, we will elucidate the development of machine learning methods, especially the visual representation mechanism in deep learning on recognition tasks. Various AI-image analysis applications in endoscopy, radiology, and pathology are covered in gastroenterology and hepatology and reveal the enormous potentials for AI in assisting diagnosis, prognosis, and treatment. We also discuss the promises as well as pitfalls for AI in medical image analysis and pointing out future research directions.

引用

页码：31 / 38

页数：8

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