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Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology
Artificial intelligence (AI) is an umbrella term used to describe a cluster of interrelated fields. Machine learning (ML) refers to a model that learns from past data to predict future data. Medicine and particularly gastroenterology and hepatology, are data-rich fields with extensive data repositor...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515803/ https://www.ncbi.nlm.nih.gov/pubmed/34712027 http://dx.doi.org/10.3748/wjg.v27.i37.6191 |
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author | Christou, Chrysanthos D Tsoulfas, Georgios |
author_facet | Christou, Chrysanthos D Tsoulfas, Georgios |
author_sort | Christou, Chrysanthos D |
collection | PubMed |
description | Artificial intelligence (AI) is an umbrella term used to describe a cluster of interrelated fields. Machine learning (ML) refers to a model that learns from past data to predict future data. Medicine and particularly gastroenterology and hepatology, are data-rich fields with extensive data repositories, and therefore fruitful ground for AI/ML-based software applications. In this study, we comprehensively review the current applications of AI/ML-based models in these fields and the opportunities that arise from their application. Specifically, we refer to the applications of AI/ML-based models in prevention, diagnosis, management, and prognosis of gastrointestinal bleeding, inflammatory bowel diseases, gastrointestinal premalignant and malignant lesions, other nonmalignant gastrointestinal lesions and diseases, hepatitis B and C infection, chronic liver diseases, hepatocellular carcinoma, cholangiocarcinoma, and primary sclerosing cholangitis. At the same time, we identify the major challenges that restrain the widespread use of these models in healthcare in an effort to explore ways to overcome them. Notably, we elaborate on the concerns regarding intrinsic biases, data protection, cybersecurity, intellectual property, liability, ethical challenges, and transparency. Even at a slower pace than anticipated, AI is infiltrating the healthcare industry. AI in healthcare will become a reality, and every physician will have to engage with it by necessity. |
format | Online Article Text |
id | pubmed-8515803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-85158032021-10-27 Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology Christou, Chrysanthos D Tsoulfas, Georgios World J Gastroenterol Review Artificial intelligence (AI) is an umbrella term used to describe a cluster of interrelated fields. Machine learning (ML) refers to a model that learns from past data to predict future data. Medicine and particularly gastroenterology and hepatology, are data-rich fields with extensive data repositories, and therefore fruitful ground for AI/ML-based software applications. In this study, we comprehensively review the current applications of AI/ML-based models in these fields and the opportunities that arise from their application. Specifically, we refer to the applications of AI/ML-based models in prevention, diagnosis, management, and prognosis of gastrointestinal bleeding, inflammatory bowel diseases, gastrointestinal premalignant and malignant lesions, other nonmalignant gastrointestinal lesions and diseases, hepatitis B and C infection, chronic liver diseases, hepatocellular carcinoma, cholangiocarcinoma, and primary sclerosing cholangitis. At the same time, we identify the major challenges that restrain the widespread use of these models in healthcare in an effort to explore ways to overcome them. Notably, we elaborate on the concerns regarding intrinsic biases, data protection, cybersecurity, intellectual property, liability, ethical challenges, and transparency. Even at a slower pace than anticipated, AI is infiltrating the healthcare industry. AI in healthcare will become a reality, and every physician will have to engage with it by necessity. Baishideng Publishing Group Inc 2021-10-07 2021-10-07 /pmc/articles/PMC8515803/ /pubmed/34712027 http://dx.doi.org/10.3748/wjg.v27.i37.6191 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Review Christou, Chrysanthos D Tsoulfas, Georgios Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title | Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title_full | Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title_fullStr | Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title_full_unstemmed | Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title_short | Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
title_sort | challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515803/ https://www.ncbi.nlm.nih.gov/pubmed/34712027 http://dx.doi.org/10.3748/wjg.v27.i37.6191 |
work_keys_str_mv | AT christouchrysanthosd challengesandopportunitiesintheapplicationofartificialintelligenceingastroenterologyandhepatology AT tsoulfasgeorgios challengesandopportunitiesintheapplicationofartificialintelligenceingastroenterologyandhepatology |