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Artificial intelligence in gastric cancer: Application and future perspectives
Gastric cancer is the fourth leading cause of cancer-related mortality across the globe, with a 5-year survival rate of less than 40%. In recent years, several applications of artificial intelligence (AI) have emerged in the gastric cancer field based on its efficient computational power and learnin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520602/ https://www.ncbi.nlm.nih.gov/pubmed/33024393 http://dx.doi.org/10.3748/wjg.v26.i36.5408 |
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author | Niu, Peng-Hui Zhao, Lu-Lu Wu, Hong-Liang Zhao, Dong-Bing Chen, Ying-Tai |
author_facet | Niu, Peng-Hui Zhao, Lu-Lu Wu, Hong-Liang Zhao, Dong-Bing Chen, Ying-Tai |
author_sort | Niu, Peng-Hui |
collection | PubMed |
description | Gastric cancer is the fourth leading cause of cancer-related mortality across the globe, with a 5-year survival rate of less than 40%. In recent years, several applications of artificial intelligence (AI) have emerged in the gastric cancer field based on its efficient computational power and learning capacities, such as image-based diagnosis and prognosis prediction. AI-assisted diagnosis includes pathology, endoscopy, and computerized tomography, while researchers in the prognosis circle focus on recurrence, metastasis, and survival prediction. In this review, a comprehensive literature search was performed on articles published up to April 2020 from the databases of PubMed, Embase, Web of Science, and the Cochrane Library. Thereby the current status of AI-applications was systematically summarized in gastric cancer. Moreover, future directions that target this field were also analyzed to overcome the risk of overfitting AI models and enhance their accuracy as well as the applicability in clinical practice. |
format | Online Article Text |
id | pubmed-7520602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-75206022020-10-05 Artificial intelligence in gastric cancer: Application and future perspectives Niu, Peng-Hui Zhao, Lu-Lu Wu, Hong-Liang Zhao, Dong-Bing Chen, Ying-Tai World J Gastroenterol Minireviews Gastric cancer is the fourth leading cause of cancer-related mortality across the globe, with a 5-year survival rate of less than 40%. In recent years, several applications of artificial intelligence (AI) have emerged in the gastric cancer field based on its efficient computational power and learning capacities, such as image-based diagnosis and prognosis prediction. AI-assisted diagnosis includes pathology, endoscopy, and computerized tomography, while researchers in the prognosis circle focus on recurrence, metastasis, and survival prediction. In this review, a comprehensive literature search was performed on articles published up to April 2020 from the databases of PubMed, Embase, Web of Science, and the Cochrane Library. Thereby the current status of AI-applications was systematically summarized in gastric cancer. Moreover, future directions that target this field were also analyzed to overcome the risk of overfitting AI models and enhance their accuracy as well as the applicability in clinical practice. Baishideng Publishing Group Inc 2020-09-28 2020-09-28 /pmc/articles/PMC7520602/ /pubmed/33024393 http://dx.doi.org/10.3748/wjg.v26.i36.5408 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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. |
spellingShingle | Minireviews Niu, Peng-Hui Zhao, Lu-Lu Wu, Hong-Liang Zhao, Dong-Bing Chen, Ying-Tai Artificial intelligence in gastric cancer: Application and future perspectives |
title | Artificial intelligence in gastric cancer: Application and future perspectives |
title_full | Artificial intelligence in gastric cancer: Application and future perspectives |
title_fullStr | Artificial intelligence in gastric cancer: Application and future perspectives |
title_full_unstemmed | Artificial intelligence in gastric cancer: Application and future perspectives |
title_short | Artificial intelligence in gastric cancer: Application and future perspectives |
title_sort | artificial intelligence in gastric cancer: application and future perspectives |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520602/ https://www.ncbi.nlm.nih.gov/pubmed/33024393 http://dx.doi.org/10.3748/wjg.v26.i36.5408 |
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