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Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment
In recent years, the advantages of artificial intelligence (AI) in data processing and model analysis have emerged in the medical field, enabled by computer technology developments and the integration of multiple disciplines. The application of AI in the medical field has gradually deepened and broa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100834/ https://www.ncbi.nlm.nih.gov/pubmed/33968664 http://dx.doi.org/10.21037/tau-20-1405 |
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author | Tan, Jun Qin, Feng Yuan, Jiuhong |
author_facet | Tan, Jun Qin, Feng Yuan, Jiuhong |
author_sort | Tan, Jun |
collection | PubMed |
description | In recent years, the advantages of artificial intelligence (AI) in data processing and model analysis have emerged in the medical field, enabled by computer technology developments and the integration of multiple disciplines. The application of AI in the medical field has gradually deepened and broadened. Among them, the development of clinical medicine intelligent decision-making is the fastest. The advantage of clinical medicine intelligent decision-making is to make the diagnosis faster and more accurate on the basis of certain information. Urine detection technologies, such as urine proteomics, urine metabolomics, and urine RNomics, have developed rapidly with the advancements in omics and medical tests. Advances in urine testing have made it possible to obtain a wealth of information from easily accessible urine. However, it has always been a problem to extract effective information from this information and use it. AI technology provides the possibility to process and use the information in urine. AI, combined with urine detection, not only provides new possibilities for precise and individual diagnosis and disease treatment, but also helps promote non-invasive diagnosis and treatment. This article reviews the research and applications of AI combined with urine detection for disease diagnosis and treatment and discusses its existing problems and future development. |
format | Online Article Text |
id | pubmed-8100834 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-81008342021-05-07 Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment Tan, Jun Qin, Feng Yuan, Jiuhong Transl Androl Urol Review Article In recent years, the advantages of artificial intelligence (AI) in data processing and model analysis have emerged in the medical field, enabled by computer technology developments and the integration of multiple disciplines. The application of AI in the medical field has gradually deepened and broadened. Among them, the development of clinical medicine intelligent decision-making is the fastest. The advantage of clinical medicine intelligent decision-making is to make the diagnosis faster and more accurate on the basis of certain information. Urine detection technologies, such as urine proteomics, urine metabolomics, and urine RNomics, have developed rapidly with the advancements in omics and medical tests. Advances in urine testing have made it possible to obtain a wealth of information from easily accessible urine. However, it has always been a problem to extract effective information from this information and use it. AI technology provides the possibility to process and use the information in urine. AI, combined with urine detection, not only provides new possibilities for precise and individual diagnosis and disease treatment, but also helps promote non-invasive diagnosis and treatment. This article reviews the research and applications of AI combined with urine detection for disease diagnosis and treatment and discusses its existing problems and future development. AME Publishing Company 2021-04 /pmc/articles/PMC8100834/ /pubmed/33968664 http://dx.doi.org/10.21037/tau-20-1405 Text en 2021 Translational Andrology and Urology. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Review Article Tan, Jun Qin, Feng Yuan, Jiuhong Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title | Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title_full | Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title_fullStr | Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title_full_unstemmed | Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title_short | Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
title_sort | current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100834/ https://www.ncbi.nlm.nih.gov/pubmed/33968664 http://dx.doi.org/10.21037/tau-20-1405 |
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