%0 Journal Article
%@ 09298673
%A Kumar, R.
%A Khan, F.U.
%A Sharma, A.
%A Aziz, I.B.A.
%A Poddar, N.K.
%D 2022
%F scholars:17786
%I Bentham Science Publishers
%J Current Medicinal Chemistry
%K artificial intelligence; capsule endoscopy; clustering algorithm; decision support system; electronic medical record; gastrointestinal disease; human; intestinal bleeding; lesions and defects; liver disease; pancreas disease; predictive model; prognosis; Review; risk assessment; supervised machine learning; algorithm; artificial intelligence; gastroenterology, Algorithms; Artificial Intelligence; Gastroenterology; Gastrointestinal Diseases; Humans; Pancreatic Diseases
%N 1
%P 66-85
%R 10.2174/0929867328666210405114938
%T Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases
%U https://khub.utp.edu.my/scholars/17786/
%V 29
%X There has been substantial progress in artificial intelligence (AI) algorithms and their medical sciences applications in the last two decades. AI-assisted programs have already been established for remote health monitoring using sensors and smartphones. A variety of AI-based prediction models are available for gastrointestinal, inflammatory, non-malignant diseases, and bowel bleeding using wireless capsule endoscopy, hepatitis-associated fibrosis using electronic medical records, and pancreatic carcinoma utilizing endoscopic ultrasounds. AI-based models may be of immense help for healthcare professionals in the identification, analysis, and decision support using endoscopic images to establish prognosis and risk assessment of patients� treatment employing multiple factors. Enough randomized clinical trials are warranted to establish the efficacy of AI-algorithms assisted and non-AI-based treatments before approval of such techniques from medical regulatory authorities. In this article, available AI approaches and AI-based prediction models for detecting gastrointestinal, hepatic, and pancreatic diseases are reviewed. The limitations of AI techniques in such diseases� prognosis, risk assessment, and decision support are discussed. © 2022 Bentham Science Publishers.
%Z cited By 6