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Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response
In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be processed by traditional methods. The proposed method is...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890881/ https://www.ncbi.nlm.nih.gov/pubmed/35251298 http://dx.doi.org/10.1155/2022/6927170 |
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author | Al-Khasawneh, Mahmoud Ahmad Bukhari, Amal Khasawneh, Ahmad M. |
author_facet | Al-Khasawneh, Mahmoud Ahmad Bukhari, Amal Khasawneh, Ahmad M. |
author_sort | Al-Khasawneh, Mahmoud Ahmad |
collection | PubMed |
description | In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be processed by traditional methods. The proposed method is based on classifying data into several classes using the data weight derived from the features extracted from the big data. Three important criteria were used to evaluate the study as well as to benchmark the current study with previous studies using a standard dataset. |
format | Online Article Text |
id | pubmed-8890881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-88908812022-03-03 Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response Al-Khasawneh, Mahmoud Ahmad Bukhari, Amal Khasawneh, Ahmad M. Comput Math Methods Med Research Article In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be processed by traditional methods. The proposed method is based on classifying data into several classes using the data weight derived from the features extracted from the big data. Three important criteria were used to evaluate the study as well as to benchmark the current study with previous studies using a standard dataset. Hindawi 2022-02-23 /pmc/articles/PMC8890881/ /pubmed/35251298 http://dx.doi.org/10.1155/2022/6927170 Text en Copyright © 2022 Mahmoud Ahmad Al-Khasawneh et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Al-Khasawneh, Mahmoud Ahmad Bukhari, Amal Khasawneh, Ahmad M. Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title | Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title_full | Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title_fullStr | Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title_full_unstemmed | Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title_short | Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response |
title_sort | effective of smart mathematical model by machine learning classifier on big data in healthcare fast response |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890881/ https://www.ncbi.nlm.nih.gov/pubmed/35251298 http://dx.doi.org/10.1155/2022/6927170 |
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