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A comprehensive analysis of healthcare big data management, analytics and scientific programming

Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of health...

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Main Authors: Nazir, Shah, Khan, Sulaiman, Khan, Habib Ullah, Ali, Shaukat, Garcia-Magarino, Ivan, Atan, Rodziah, Nawaz, Muhammad
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers 2020
Online Access:http://psasir.upm.edu.my/id/eprint/87585/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/87585/
https://ieeexplore.ieee.org/document/9096305
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spelling my.upm.eprints.875852022-07-06T07:38:00Z http://psasir.upm.edu.my/id/eprint/87585/ A comprehensive analysis of healthcare big data management, analytics and scientific programming Nazir, Shah Khan, Sulaiman Khan, Habib Ullah Ali, Shaukat Garcia-Magarino, Ivan Atan, Rodziah Nawaz, Muhammad Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015 - 2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly. Institute of Electrical and Electronics Engineers 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87585/1/ABSTRACT.pdf Nazir, Shah and Khan, Sulaiman and Khan, Habib Ullah and Ali, Shaukat and Garcia-Magarino, Ivan and Atan, Rodziah and Nawaz, Muhammad (2020) A comprehensive analysis of healthcare big data management, analytics and scientific programming. IEEE Access, 8. 95714 - 95733. ISSN 2169-3536 https://ieeexplore.ieee.org/document/9096305 10.1109/ACCESS.2020.2995572
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015 - 2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly.
format Article
author Nazir, Shah
Khan, Sulaiman
Khan, Habib Ullah
Ali, Shaukat
Garcia-Magarino, Ivan
Atan, Rodziah
Nawaz, Muhammad
spellingShingle Nazir, Shah
Khan, Sulaiman
Khan, Habib Ullah
Ali, Shaukat
Garcia-Magarino, Ivan
Atan, Rodziah
Nawaz, Muhammad
A comprehensive analysis of healthcare big data management, analytics and scientific programming
author_facet Nazir, Shah
Khan, Sulaiman
Khan, Habib Ullah
Ali, Shaukat
Garcia-Magarino, Ivan
Atan, Rodziah
Nawaz, Muhammad
author_sort Nazir, Shah
title A comprehensive analysis of healthcare big data management, analytics and scientific programming
title_short A comprehensive analysis of healthcare big data management, analytics and scientific programming
title_full A comprehensive analysis of healthcare big data management, analytics and scientific programming
title_fullStr A comprehensive analysis of healthcare big data management, analytics and scientific programming
title_full_unstemmed A comprehensive analysis of healthcare big data management, analytics and scientific programming
title_sort comprehensive analysis of healthcare big data management, analytics and scientific programming
publisher Institute of Electrical and Electronics Engineers
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/87585/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/87585/
https://ieeexplore.ieee.org/document/9096305
_version_ 1738511958083108864
score 13.211869

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