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The Present and Future of Artificial Intelligence in Urological Cancer
Artificial intelligence has drawn more and more attention for both research and application in the field of medicine. It has considerable potential for urological cancer detection, therapy, and prognosis prediction due to its ability to choose features in data to complete a particular task autonomou...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419644/ https://www.ncbi.nlm.nih.gov/pubmed/37568397 http://dx.doi.org/10.3390/jcm12154995 |
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author | Liu, Xun Shi, Jianxi Li, Zhaopeng Huang, Yue Zhang, Zhihong Zhang, Changwen |
author_facet | Liu, Xun Shi, Jianxi Li, Zhaopeng Huang, Yue Zhang, Zhihong Zhang, Changwen |
author_sort | Liu, Xun |
collection | PubMed |
description | Artificial intelligence has drawn more and more attention for both research and application in the field of medicine. It has considerable potential for urological cancer detection, therapy, and prognosis prediction due to its ability to choose features in data to complete a particular task autonomously. Although the clinical application of AI is still immature and faces drawbacks such as insufficient data and a lack of prospective clinical trials, AI will play an essential role in individualization and the whole management of cancers as research progresses. In this review, we summarize the applications and studies of AI in major urological cancers, including tumor diagnosis, treatment, and prognosis prediction. Moreover, we discuss the current challenges and future applications of AI. |
format | Online Article Text |
id | pubmed-10419644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104196442023-08-12 The Present and Future of Artificial Intelligence in Urological Cancer Liu, Xun Shi, Jianxi Li, Zhaopeng Huang, Yue Zhang, Zhihong Zhang, Changwen J Clin Med Review Artificial intelligence has drawn more and more attention for both research and application in the field of medicine. It has considerable potential for urological cancer detection, therapy, and prognosis prediction due to its ability to choose features in data to complete a particular task autonomously. Although the clinical application of AI is still immature and faces drawbacks such as insufficient data and a lack of prospective clinical trials, AI will play an essential role in individualization and the whole management of cancers as research progresses. In this review, we summarize the applications and studies of AI in major urological cancers, including tumor diagnosis, treatment, and prognosis prediction. Moreover, we discuss the current challenges and future applications of AI. MDPI 2023-07-29 /pmc/articles/PMC10419644/ /pubmed/37568397 http://dx.doi.org/10.3390/jcm12154995 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Liu, Xun Shi, Jianxi Li, Zhaopeng Huang, Yue Zhang, Zhihong Zhang, Changwen The Present and Future of Artificial Intelligence in Urological Cancer |
title | The Present and Future of Artificial Intelligence in Urological Cancer |
title_full | The Present and Future of Artificial Intelligence in Urological Cancer |
title_fullStr | The Present and Future of Artificial Intelligence in Urological Cancer |
title_full_unstemmed | The Present and Future of Artificial Intelligence in Urological Cancer |
title_short | The Present and Future of Artificial Intelligence in Urological Cancer |
title_sort | present and future of artificial intelligence in urological cancer |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419644/ https://www.ncbi.nlm.nih.gov/pubmed/37568397 http://dx.doi.org/10.3390/jcm12154995 |
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