Open AccessArtificial intelligence in gastroenterology and hepatology: Status and challenges
Author(s) -
Jiasheng Cao,
Ziyi Lu,
Mingyu Chen,
Bin Zhang,
Sarun Juengpanich,
Jiahao Hu,
Shijie Li,
Win Topatana,
Xue-Yin Zhou,
Feng Xu,
Jiliang Shen,
Yu Liu,
Xiujun Cai
Publication year - 2021
Publication title -
world journal of gastroenterology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.427
H-Index - 155
eISSN - 2219-2840
pISSN - 1007-9327
DOI - 10.3748/wjg.v27.i16.1664
Subject(s) - hepatology , medicine , medical physics , medline , computer science , artificial intelligence , radiology , political science , law
Originally proposed by John McCarthy in 1955, artificial intelligence (AI) has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and digital images. Doctors are paying attention to AI technologies for various diseases in the fields of gastroenterology and hepatology. This review will illustrate AI technology procedures for medical image analysis, including data processing, model establishment, and model validation. Furthermore, we will summarize AI applications in endoscopy, radiology, and pathology, such as detecting and evaluating lesions, facilitating treatment, and predicting treatment response and prognosis with excellent model performance. The current challenges for AI in clinical application include potential inherent bias in retrospective studies that requires larger samples for validation, ethics and legal concerns, and the incomprehensibility of the output results. Therefore, doctors and researchers should cooperate to address the current challenges and carry out further investigations to develop more accurate AI tools for improved clinical applications.