eprintid: 17786
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/77/86
datestamp: 2023-12-19 03:24:06
lastmod: 2023-12-19 03:24:06
status_changed: 2023-12-19 03:08:40
type: article
metadata_visibility: show
creators_name: Kumar, R.
creators_name: Khan, F.U.
creators_name: Sharma, A.
creators_name: Aziz, I.B.A.
creators_name: Poddar, N.K.
title: Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases
ispublished: pub
keywords: 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
note: cited By 6
abstract: 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.
date: 2022
publisher: Bentham Science Publishers
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122367202&doi=10.2174%2f0929867328666210405114938&partnerID=40&md5=5d90a6275dd81a9884a0bdb682082b86
id_number: 10.2174/0929867328666210405114938
full_text_status: none
publication: Current Medicinal Chemistry
volume: 29
number: 1
pagerange: 66-85
refereed: TRUE
issn: 09298673
citation:   Kumar, R. and Khan, F.U. and Sharma, A. and Aziz, I.B.A. and Poddar, N.K.  (2022) Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases.  Current Medicinal Chemistry, 29 (1).  pp. 66-85.  ISSN 09298673