Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases

• Main Authors: Kumar, R., Khan, F.U., Sharma, A., Aziz, I.B.A., Poddar, N.K.
• Format: Article
• Published: Bentham Science Publishers 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122367202&doi=10.2174%2f0929867328666210405114938&partnerID=40&md5=5d90a6275dd81a9884a0bdb682082b86; http://eprints.utp.edu.my/28933/

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.