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Artificial Intelligence-Based Medical Data Mining
Understanding published unstructured textual data using traditional text mining approaches and tools is becoming a challenging issue due to the rapid increase in electronic open-source publications. The application of data mining techniques in the medical sciences is an emerging trend; however, trad...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501106/ https://www.ncbi.nlm.nih.gov/pubmed/36143144 http://dx.doi.org/10.3390/jpm12091359 |
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author | Zia, Amjad Aziz, Muzzamil Popa, Ioana Khan, Sabih Ahmed Hamedani, Amirreza Fazely Asif, Abdul R. |
author_facet | Zia, Amjad Aziz, Muzzamil Popa, Ioana Khan, Sabih Ahmed Hamedani, Amirreza Fazely Asif, Abdul R. |
author_sort | Zia, Amjad |
collection | PubMed |
description | Understanding published unstructured textual data using traditional text mining approaches and tools is becoming a challenging issue due to the rapid increase in electronic open-source publications. The application of data mining techniques in the medical sciences is an emerging trend; however, traditional text-mining approaches are insufficient to cope with the current upsurge in the volume of published data. Therefore, artificial intelligence-based text mining tools are being developed and used to process large volumes of data and to explore the hidden features and correlations in the data. This review provides a clear-cut and insightful understanding of how artificial intelligence-based data-mining technology is being used to analyze medical data. We also describe a standard process of data mining based on CRISP-DM (Cross-Industry Standard Process for Data Mining) and the most common tools/libraries available for each step of medical data mining. |
format | Online Article Text |
id | pubmed-9501106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95011062022-09-24 Artificial Intelligence-Based Medical Data Mining Zia, Amjad Aziz, Muzzamil Popa, Ioana Khan, Sabih Ahmed Hamedani, Amirreza Fazely Asif, Abdul R. J Pers Med Review Understanding published unstructured textual data using traditional text mining approaches and tools is becoming a challenging issue due to the rapid increase in electronic open-source publications. The application of data mining techniques in the medical sciences is an emerging trend; however, traditional text-mining approaches are insufficient to cope with the current upsurge in the volume of published data. Therefore, artificial intelligence-based text mining tools are being developed and used to process large volumes of data and to explore the hidden features and correlations in the data. This review provides a clear-cut and insightful understanding of how artificial intelligence-based data-mining technology is being used to analyze medical data. We also describe a standard process of data mining based on CRISP-DM (Cross-Industry Standard Process for Data Mining) and the most common tools/libraries available for each step of medical data mining. MDPI 2022-08-24 /pmc/articles/PMC9501106/ /pubmed/36143144 http://dx.doi.org/10.3390/jpm12091359 Text en © 2022 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 Zia, Amjad Aziz, Muzzamil Popa, Ioana Khan, Sabih Ahmed Hamedani, Amirreza Fazely Asif, Abdul R. Artificial Intelligence-Based Medical Data Mining |
title | Artificial Intelligence-Based Medical Data Mining |
title_full | Artificial Intelligence-Based Medical Data Mining |
title_fullStr | Artificial Intelligence-Based Medical Data Mining |
title_full_unstemmed | Artificial Intelligence-Based Medical Data Mining |
title_short | Artificial Intelligence-Based Medical Data Mining |
title_sort | artificial intelligence-based medical data mining |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501106/ https://www.ncbi.nlm.nih.gov/pubmed/36143144 http://dx.doi.org/10.3390/jpm12091359 |
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