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Applications of artificial intelligence in urological setting: a hopeful path to improved care
Artificial intelligence (AI) has been introduced in urology research and practice. Application of AI leads to better accuracy of disease diagnosis and predictive model for monitoring of responses to medical treatments. This mini-review article aims to summarize current applications and development o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Exercise Rehabilitation
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566099/ https://www.ncbi.nlm.nih.gov/pubmed/34805018 http://dx.doi.org/10.12965/jer.2142596.298 |
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author | Eun, Sung-Jong Kim, Jayoung Kim, Khae Hawn |
author_facet | Eun, Sung-Jong Kim, Jayoung Kim, Khae Hawn |
author_sort | Eun, Sung-Jong |
collection | PubMed |
description | Artificial intelligence (AI) has been introduced in urology research and practice. Application of AI leads to better accuracy of disease diagnosis and predictive model for monitoring of responses to medical treatments. This mini-review article aims to summarize current applications and development of AI in urology setting, in particular for diagnosis and treatment of urological diseases. This review will introduce that machine learning algorithm-based models will enhance the prediction accuracy for various bladder diseases including interstitial cystitis, bladder cancer, and reproductive urology. |
format | Online Article Text |
id | pubmed-8566099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Society of Exercise Rehabilitation |
record_format | MEDLINE/PubMed |
spelling | pubmed-85660992021-11-18 Applications of artificial intelligence in urological setting: a hopeful path to improved care Eun, Sung-Jong Kim, Jayoung Kim, Khae Hawn J Exerc Rehabil Review Article Artificial intelligence (AI) has been introduced in urology research and practice. Application of AI leads to better accuracy of disease diagnosis and predictive model for monitoring of responses to medical treatments. This mini-review article aims to summarize current applications and development of AI in urology setting, in particular for diagnosis and treatment of urological diseases. This review will introduce that machine learning algorithm-based models will enhance the prediction accuracy for various bladder diseases including interstitial cystitis, bladder cancer, and reproductive urology. Korean Society of Exercise Rehabilitation 2021-10-26 /pmc/articles/PMC8566099/ /pubmed/34805018 http://dx.doi.org/10.12965/jer.2142596.298 Text en Copyright © 2021 Korean Society of Exercise Rehabilitation https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Eun, Sung-Jong Kim, Jayoung Kim, Khae Hawn Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title | Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title_full | Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title_fullStr | Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title_full_unstemmed | Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title_short | Applications of artificial intelligence in urological setting: a hopeful path to improved care |
title_sort | applications of artificial intelligence in urological setting: a hopeful path to improved care |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566099/ https://www.ncbi.nlm.nih.gov/pubmed/34805018 http://dx.doi.org/10.12965/jer.2142596.298 |
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