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Artificial intelligence applications in pathological diagnosis of gastric cancer
Globally, gastric cancer is the third leading cause of death from tumors. Prevention and individualized treatment are considered to be the best options for reducing the mortality rate of gastric cancer. Artificial intelligence (AI) technology has been widely used in the field of gastric cancer, incl...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816967/ https://www.ncbi.nlm.nih.gov/pubmed/36619448 http://dx.doi.org/10.1016/j.heliyon.2022.e12431 |
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author | Deng, Yang Qin, Hang-Yu Zhou, Yan-Yan Liu, Hong-Hong Jiang, Yong Liu, Jian-Ping Bao, Ji |
author_facet | Deng, Yang Qin, Hang-Yu Zhou, Yan-Yan Liu, Hong-Hong Jiang, Yong Liu, Jian-Ping Bao, Ji |
author_sort | Deng, Yang |
collection | PubMed |
description | Globally, gastric cancer is the third leading cause of death from tumors. Prevention and individualized treatment are considered to be the best options for reducing the mortality rate of gastric cancer. Artificial intelligence (AI) technology has been widely used in the field of gastric cancer, including diagnosis, prognosis, and image analysis. Eligible papers were identified from PubMed and IEEE up to April 13, 2022. Through the comparison of these articles, the application status of AI technology in the diagnosis of gastric cancer was summarized, including application types, application scenarios, advantages and limitations. This review presents the current state and role of AI in the diagnosis of gastric cancer based on four aspects: 1) accurate sampling from early diagnosis (endoscopy), 2) digital pathological diagnosis, 3) molecules and genes, and 4) clinical big data analysis and prognosis prediction. AI plays a very important role in facilitating the diagnosis of gastric cancer; however, it also has shortcomings such as interpretability. The purpose of this review is to provide assistance to researchers working in this domain. |
format | Online Article Text |
id | pubmed-9816967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98169672023-01-07 Artificial intelligence applications in pathological diagnosis of gastric cancer Deng, Yang Qin, Hang-Yu Zhou, Yan-Yan Liu, Hong-Hong Jiang, Yong Liu, Jian-Ping Bao, Ji Heliyon Review Article Globally, gastric cancer is the third leading cause of death from tumors. Prevention and individualized treatment are considered to be the best options for reducing the mortality rate of gastric cancer. Artificial intelligence (AI) technology has been widely used in the field of gastric cancer, including diagnosis, prognosis, and image analysis. Eligible papers were identified from PubMed and IEEE up to April 13, 2022. Through the comparison of these articles, the application status of AI technology in the diagnosis of gastric cancer was summarized, including application types, application scenarios, advantages and limitations. This review presents the current state and role of AI in the diagnosis of gastric cancer based on four aspects: 1) accurate sampling from early diagnosis (endoscopy), 2) digital pathological diagnosis, 3) molecules and genes, and 4) clinical big data analysis and prognosis prediction. AI plays a very important role in facilitating the diagnosis of gastric cancer; however, it also has shortcomings such as interpretability. The purpose of this review is to provide assistance to researchers working in this domain. Elsevier 2022-12-19 /pmc/articles/PMC9816967/ /pubmed/36619448 http://dx.doi.org/10.1016/j.heliyon.2022.e12431 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Deng, Yang Qin, Hang-Yu Zhou, Yan-Yan Liu, Hong-Hong Jiang, Yong Liu, Jian-Ping Bao, Ji Artificial intelligence applications in pathological diagnosis of gastric cancer |
title | Artificial intelligence applications in pathological diagnosis of gastric cancer |
title_full | Artificial intelligence applications in pathological diagnosis of gastric cancer |
title_fullStr | Artificial intelligence applications in pathological diagnosis of gastric cancer |
title_full_unstemmed | Artificial intelligence applications in pathological diagnosis of gastric cancer |
title_short | Artificial intelligence applications in pathological diagnosis of gastric cancer |
title_sort | artificial intelligence applications in pathological diagnosis of gastric cancer |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816967/ https://www.ncbi.nlm.nih.gov/pubmed/36619448 http://dx.doi.org/10.1016/j.heliyon.2022.e12431 |
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