Literature DB >> 31593701

Application of Artificial Intelligence to Gastroenterology and Hepatology.

Catherine Le Berre1, William J Sandborn2, Sabeur Aridhi3, Marie-Dominique Devignes3, Laure Fournier4, Malika Smaïl-Tabbone3, Silvio Danese5, Laurent Peyrin-Biroulet6.   

Abstract

Since 2010, substantial progress has been made in artificial intelligence (AI) and its application to medicine. AI is explored in gastroenterology for endoscopic analysis of lesions, in detection of cancer, and to facilitate the analysis of inflammatory lesions or gastrointestinal bleeding during wireless capsule endoscopy. AI is also tested to assess liver fibrosis and to differentiate patients with pancreatic cancer from those with pancreatitis. AI might also be used to establish prognoses of patients or predict their response to treatments, based on multiple factors. We review the ways in which AI may help physicians make a diagnosis or establish a prognosis and discuss its limitations, knowing that further randomized controlled studies will be required before the approval of AI techniques by the health authorities.
Copyright © 2020 AGA Institute. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Deep Learning; Digestive System; Machine Learning; Neural Network

Mesh:

Year:  2019        PMID: 31593701     DOI: 10.1053/j.gastro.2019.08.058

Source DB:  PubMed          Journal:  Gastroenterology        ISSN: 0016-5085            Impact factor:   22.682


  66 in total

Review 1.  What is new in computer vision and artificial intelligence in medical image analysis applications.

Authors:  Jimena Olveres; Germán González; Fabian Torres; José Carlos Moreno-Tagle; Erik Carbajal-Degante; Alejandro Valencia-Rodríguez; Nahum Méndez-Sánchez; Boris Escalante-Ramírez
Journal:  Quant Imaging Med Surg       Date:  2021-08

Review 2.  The overview of the deep learning integrated into the medical imaging of liver: a review.

Authors:  Kailai Xiang; Baihui Jiang; Dong Shang
Journal:  Hepatol Int       Date:  2021-07-15       Impact factor: 6.047

3.  UEG Week 2020 Poster Presentations.

Authors: 
Journal:  United European Gastroenterol J       Date:  2020-10       Impact factor: 4.623

Review 4.  Advanced EUS Imaging Techniques.

Authors:  Irina M Cazacu; Adrian Saftoiu; Manoop S Bhutani
Journal:  Dig Dis Sci       Date:  2022-04-22       Impact factor: 3.199

5.  A deep-learning-based unsupervised model on esophageal manometry using variational autoencoder.

Authors:  Wenjun Kou; Dustin A Carlson; Alexandra J Baumann; Erica Donnan; Yuan Luo; John E Pandolfino; Mozziyar Etemadi
Journal:  Artif Intell Med       Date:  2021-01-05       Impact factor: 5.326

6.  Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

Authors:  Gulseren Seven; Gokhan Silahtaroglu; Koray Kochan; Ali Tuzun Ince; Dilek Sema Arici; Hakan Senturk
Journal:  Dig Dis Sci       Date:  2021-02-06       Impact factor: 3.199

Review 7.  Artificial Intelligence in Medicine: Chances and Challenges for Wide Clinical Adoption.

Authors:  Julian Varghese
Journal:  Visc Med       Date:  2020-10-12

8.  Gut microbiome-based supervised machine learning for clinical diagnosis of inflammatory bowel diseases.

Authors:  Ishan Manandhar; Ahmad Alimadadi; Sachin Aryal; Patricia B Munroe; Bina Joe; Xi Cheng
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2021-01-13       Impact factor: 4.052

9.  Evaluation of Performance in Colon Capsule Endoscopy Reading by Endoscopy Nurses.

Authors:  Yukiko Handa; Konosuke Nakaji; Kayo Hyogo; Makiko Kawakami; Tomomi Yamamoto; Akiko Fujiwara; Rika Kanda; Motoyasu Osawa; Osamu Handa; Hiroshi Matsumoto; Eiji Umegaki; Akiko Shiotani
Journal:  Can J Gastroenterol Hepatol       Date:  2021-04-28

10.  Regarding: Shung et al: Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

Authors:  Hyun-Seok Kim; Frederick B Peng; Juan David Gomez Cifuentes
Journal:  Gastroenterology       Date:  2020-03-19       Impact factor: 22.682

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.