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Status quo and future prospects of artificial neural network from the perspective of gastroenterologists
Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In recent years, there has been a sharp increase in research concerning ANNs in gastrointestinal (GI) diseases. This state-of-the-art technique exhibits...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173384/ https://www.ncbi.nlm.nih.gov/pubmed/34135549 http://dx.doi.org/10.3748/wjg.v27.i21.2681 |
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author | Cao, Bo Zhang, Ke-Cheng Wei, Bo Chen, Lin |
author_facet | Cao, Bo Zhang, Ke-Cheng Wei, Bo Chen, Lin |
author_sort | Cao, Bo |
collection | PubMed |
description | Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In recent years, there has been a sharp increase in research concerning ANNs in gastrointestinal (GI) diseases. This state-of-the-art technique exhibits excellent performance in diagnosis, prognostic prediction, and treatment. Competitions between ANNs and GI experts suggest that efficiency and accuracy might be compatible in virtue of technique advancements. However, the shortcomings of ANNs are not negligible and may induce alterations in many aspects of medical practice. In this review, we introduce basic knowledge about ANNs and summarize the current achievements of ANNs in GI diseases from the perspective of gastroenterologists. Existing limitations and future directions are also proposed to optimize ANN’s clinical potential. In consideration of barriers to interdisciplinary knowledge, sophisticated concepts are discussed using plain words and metaphors to make this review more easily understood by medical practitioners and the general public. |
format | Online Article Text |
id | pubmed-8173384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-81733842021-06-15 Status quo and future prospects of artificial neural network from the perspective of gastroenterologists Cao, Bo Zhang, Ke-Cheng Wei, Bo Chen, Lin World J Gastroenterol Review Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In recent years, there has been a sharp increase in research concerning ANNs in gastrointestinal (GI) diseases. This state-of-the-art technique exhibits excellent performance in diagnosis, prognostic prediction, and treatment. Competitions between ANNs and GI experts suggest that efficiency and accuracy might be compatible in virtue of technique advancements. However, the shortcomings of ANNs are not negligible and may induce alterations in many aspects of medical practice. In this review, we introduce basic knowledge about ANNs and summarize the current achievements of ANNs in GI diseases from the perspective of gastroenterologists. Existing limitations and future directions are also proposed to optimize ANN’s clinical potential. In consideration of barriers to interdisciplinary knowledge, sophisticated concepts are discussed using plain words and metaphors to make this review more easily understood by medical practitioners and the general public. Baishideng Publishing Group Inc 2021-06-07 2021-06-07 /pmc/articles/PMC8173384/ /pubmed/34135549 http://dx.doi.org/10.3748/wjg.v27.i21.2681 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 Cao, Bo Zhang, Ke-Cheng Wei, Bo Chen, Lin Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title | Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title_full | Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title_fullStr | Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title_full_unstemmed | Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title_short | Status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
title_sort | status quo and future prospects of artificial neural network from the perspective of gastroenterologists |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173384/ https://www.ncbi.nlm.nih.gov/pubmed/34135549 http://dx.doi.org/10.3748/wjg.v27.i21.2681 |
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