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Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases
Artificial intelligence (AI) has enormous potential to support clinical routine workflows and therefore is gaining increasing popularity among medical professionals. In the field of gastroenterology, investigations on AI and computer-aided diagnosis (CAD) systems have mainly focused on the lower gas...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988236/ https://www.ncbi.nlm.nih.gov/pubmed/34739406 http://dx.doi.org/10.1097/MCG.0000000000001629 |
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author | Visaggi, Pierfrancesco de Bortoli, Nicola Barberio, Brigida Savarino, Vincenzo Oleas, Roberto Rosi, Emma M. Marchi, Santino Ribolsi, Mentore Savarino, Edoardo |
author_facet | Visaggi, Pierfrancesco de Bortoli, Nicola Barberio, Brigida Savarino, Vincenzo Oleas, Roberto Rosi, Emma M. Marchi, Santino Ribolsi, Mentore Savarino, Edoardo |
author_sort | Visaggi, Pierfrancesco |
collection | PubMed |
description | Artificial intelligence (AI) has enormous potential to support clinical routine workflows and therefore is gaining increasing popularity among medical professionals. In the field of gastroenterology, investigations on AI and computer-aided diagnosis (CAD) systems have mainly focused on the lower gastrointestinal (GI) tract. However, numerous CAD tools have been tested also in upper GI disorders showing encouraging results. The main application of AI in the upper GI tract is endoscopy; however, the need to analyze increasing loads of numerical and categorical data in short times has pushed researchers to investigate applications of AI systems in other upper GI settings, including gastroesophageal reflux disease, eosinophilic esophagitis, and motility disorders. AI and CAD systems will be increasingly incorporated into daily clinical practice in the coming years, thus at least basic notions will be soon required among physicians. For noninsiders, the working principles and potential of AI may be as fascinating as obscure. Accordingly, we reviewed systematic reviews, meta-analyses, randomized controlled trials, and original research articles regarding the performance of AI in the diagnosis of both malignant and benign esophageal and gastric diseases, also discussing essential characteristics of AI. |
format | Online Article Text |
id | pubmed-9988236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-99882362023-03-07 Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases Visaggi, Pierfrancesco de Bortoli, Nicola Barberio, Brigida Savarino, Vincenzo Oleas, Roberto Rosi, Emma M. Marchi, Santino Ribolsi, Mentore Savarino, Edoardo J Clin Gastroenterol Clinical Reviews Artificial intelligence (AI) has enormous potential to support clinical routine workflows and therefore is gaining increasing popularity among medical professionals. In the field of gastroenterology, investigations on AI and computer-aided diagnosis (CAD) systems have mainly focused on the lower gastrointestinal (GI) tract. However, numerous CAD tools have been tested also in upper GI disorders showing encouraging results. The main application of AI in the upper GI tract is endoscopy; however, the need to analyze increasing loads of numerical and categorical data in short times has pushed researchers to investigate applications of AI systems in other upper GI settings, including gastroesophageal reflux disease, eosinophilic esophagitis, and motility disorders. AI and CAD systems will be increasingly incorporated into daily clinical practice in the coming years, thus at least basic notions will be soon required among physicians. For noninsiders, the working principles and potential of AI may be as fascinating as obscure. Accordingly, we reviewed systematic reviews, meta-analyses, randomized controlled trials, and original research articles regarding the performance of AI in the diagnosis of both malignant and benign esophageal and gastric diseases, also discussing essential characteristics of AI. Lippincott Williams & Wilkins 2022-01 2021-11-04 /pmc/articles/PMC9988236/ /pubmed/34739406 http://dx.doi.org/10.1097/MCG.0000000000001629 Text en Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/) (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Clinical Reviews Visaggi, Pierfrancesco de Bortoli, Nicola Barberio, Brigida Savarino, Vincenzo Oleas, Roberto Rosi, Emma M. Marchi, Santino Ribolsi, Mentore Savarino, Edoardo Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title | Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title_full | Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title_fullStr | Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title_full_unstemmed | Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title_short | Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases |
title_sort | artificial intelligence in the diagnosis of upper gastrointestinal diseases |
topic | Clinical Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988236/ https://www.ncbi.nlm.nih.gov/pubmed/34739406 http://dx.doi.org/10.1097/MCG.0000000000001629 |
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