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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...

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Detalles Bibliográficos
Autores principales: Eun, Sung-Jong, Kim, Jayoung, Kim, Khae Hawn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Exercise Rehabilitation 2021
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.
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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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