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Healthcare analytics—A literature review and proposed research agenda

This research addresses the demanding need for research in healthcare analytics, by explaining how previous studies have used big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods are combined with contemporary data science techniques to ex...

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Detalles Bibliográficos
Autores principales: Elragal, Rawan, Elragal, Ahmed, Habibipour, Abdolrasoul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585099/
https://www.ncbi.nlm.nih.gov/pubmed/37869248
http://dx.doi.org/10.3389/fdata.2023.1277976
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author Elragal, Rawan
Elragal, Ahmed
Habibipour, Abdolrasoul
author_facet Elragal, Rawan
Elragal, Ahmed
Habibipour, Abdolrasoul
author_sort Elragal, Rawan
collection PubMed
description This research addresses the demanding need for research in healthcare analytics, by explaining how previous studies have used big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods are combined with contemporary data science techniques to examine the literature, identify research gaps, and propose a research agenda for researchers, academic institutions, and governmental healthcare organizations. The study contributes to the body of literature by providing a state-of-the-art review of healthcare analytics as well as proposing a research agenda to advance the knowledge in this area. The results of this research can be beneficial for both healthcare science and data science researchers as well as practitioners in the field.
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spelling pubmed-105850992023-10-20 Healthcare analytics—A literature review and proposed research agenda Elragal, Rawan Elragal, Ahmed Habibipour, Abdolrasoul Front Big Data Big Data This research addresses the demanding need for research in healthcare analytics, by explaining how previous studies have used big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods are combined with contemporary data science techniques to examine the literature, identify research gaps, and propose a research agenda for researchers, academic institutions, and governmental healthcare organizations. The study contributes to the body of literature by providing a state-of-the-art review of healthcare analytics as well as proposing a research agenda to advance the knowledge in this area. The results of this research can be beneficial for both healthcare science and data science researchers as well as practitioners in the field. Frontiers Media S.A. 2023-10-05 /pmc/articles/PMC10585099/ /pubmed/37869248 http://dx.doi.org/10.3389/fdata.2023.1277976 Text en Copyright © 2023 Elragal, Elragal and Habibipour. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Elragal, Rawan
Elragal, Ahmed
Habibipour, Abdolrasoul
Healthcare analytics—A literature review and proposed research agenda
title Healthcare analytics—A literature review and proposed research agenda
title_full Healthcare analytics—A literature review and proposed research agenda
title_fullStr Healthcare analytics—A literature review and proposed research agenda
title_full_unstemmed Healthcare analytics—A literature review and proposed research agenda
title_short Healthcare analytics—A literature review and proposed research agenda
title_sort healthcare analytics—a literature review and proposed research agenda
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585099/
https://www.ncbi.nlm.nih.gov/pubmed/37869248
http://dx.doi.org/10.3389/fdata.2023.1277976
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