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Magnetic resonance imaging-based artificial intelligence model in rectal cancer
Rectal magnetic resonance imaging (MRI) is the preferred method for the diagnosis of rectal cancer as recommended by the guidelines. Rectal MRI can accurately evaluate the tumor location, tumor stage, invasion depth, extramural vascular invasion, and circumferential resection margin. We summarize th...
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/PMC8117733/ https://www.ncbi.nlm.nih.gov/pubmed/34025068 http://dx.doi.org/10.3748/wjg.v27.i18.2122 |
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author | Wang, Pei-Pei Deng, Chao-Lin Wu, Bin |
author_facet | Wang, Pei-Pei Deng, Chao-Lin Wu, Bin |
author_sort | Wang, Pei-Pei |
collection | PubMed |
description | Rectal magnetic resonance imaging (MRI) is the preferred method for the diagnosis of rectal cancer as recommended by the guidelines. Rectal MRI can accurately evaluate the tumor location, tumor stage, invasion depth, extramural vascular invasion, and circumferential resection margin. We summarize the progress of research on the use of artificial intelligence (AI) in rectal cancer in recent years. AI, represented by machine learning, is being increasingly used in the medical field. The application of AI models based on high-resolution MRI in rectal cancer has been increasingly reported. In addition to staging the diagnosis and localizing radiotherapy, an increasing number of studies have reported that AI models based on high-resolution MRI can be used to predict the response to chemotherapy and prognosis of patients. |
format | Online Article Text |
id | pubmed-8117733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-81177332021-05-20 Magnetic resonance imaging-based artificial intelligence model in rectal cancer Wang, Pei-Pei Deng, Chao-Lin Wu, Bin World J Gastroenterol Minireviews Rectal magnetic resonance imaging (MRI) is the preferred method for the diagnosis of rectal cancer as recommended by the guidelines. Rectal MRI can accurately evaluate the tumor location, tumor stage, invasion depth, extramural vascular invasion, and circumferential resection margin. We summarize the progress of research on the use of artificial intelligence (AI) in rectal cancer in recent years. AI, represented by machine learning, is being increasingly used in the medical field. The application of AI models based on high-resolution MRI in rectal cancer has been increasingly reported. In addition to staging the diagnosis and localizing radiotherapy, an increasing number of studies have reported that AI models based on high-resolution MRI can be used to predict the response to chemotherapy and prognosis of patients. Baishideng Publishing Group Inc 2021-05-14 2021-05-14 /pmc/articles/PMC8117733/ /pubmed/34025068 http://dx.doi.org/10.3748/wjg.v27.i18.2122 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 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 Wang, Pei-Pei Deng, Chao-Lin Wu, Bin Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title | Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title_full | Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title_fullStr | Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title_full_unstemmed | Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title_short | Magnetic resonance imaging-based artificial intelligence model in rectal cancer |
title_sort | magnetic resonance imaging-based artificial intelligence model in rectal cancer |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117733/ https://www.ncbi.nlm.nih.gov/pubmed/34025068 http://dx.doi.org/10.3748/wjg.v27.i18.2122 |
work_keys_str_mv | AT wangpeipei magneticresonanceimagingbasedartificialintelligencemodelinrectalcancer AT dengchaolin magneticresonanceimagingbasedartificialintelligencemodelinrectalcancer AT wubin magneticresonanceimagingbasedartificialintelligencemodelinrectalcancer |