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AuthorKhan, Sulaiman
AuthorKhan, Habib Ullah
AuthorNazir, Shah
Available date2023-08-09T06:35:13Z
Publication Date2022-12-26
Publication NameScientific Reports
Identifierhttp://dx.doi.org/10.1038/s41598-022-26090-5
CitationKhan, S., Khan, H. U., & Nazir, S. (2022). Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing. Scientific Reports, 12(1), 22377.
ISSN2045-2322
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85144638039&origin=inward
URIhttp://hdl.handle.net/10576/46560
AbstractBig data has revolutionized the world by providing tremendous opportunities for a variety of applications. It contains a gigantic amount of data, especially a plethora of data types that has been significantly useful in diverse research domains. In healthcare domain, the researchers use computational devices to extract enriched relevant information from this data and develop smart applications to solve real-life problems in a timely fashion. Electronic health (eHealth) and mobile health (mHealth) facilities alongwith the availability of new computational models have enabled the doctors and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. Digital transformation of healthcare systems by using of information system, medical technology, handheld and smart wearable devices has posed many challenges to researchers and caretakers in the form of storage, minimizing treatment cost, and processing time (to extract enriched information, and minimize error rates to make optimum decisions). In this research work, the existing literature is analysed and assessed, to identify gaps that result in affecting the overall performance of the available healthcare applications. Also, it aims to suggest enhanced solutions to address these gaps. In this comprehensive systematic research work, the existing literature reported during 2011 to 2021, is thoroughly analysed for identifying the efforts made to facilitate the doctors and practitioners for diagnosing diseases using healthcare big data analytics. A set of rresearch questions are formulated to analyse the relevant articles for identifying the key features and optimum management solutions, and laterally use these analyses to achieve effective outcomes. The results of this systematic mapping conclude that despite of hard efforts made in the domains of healthcare big data analytics, the newer hybrid machine learning based systems and cloud computing-based models should be adapted to reduce treatment cost, simulation time and achieve improved quality of care. This systematic mapping will also result in enhancing the capabilities of doctors, practitioners, researchers, and policymakers to use this study as evidence for future research.
SponsorOpen Access funding provided by the Qatar National Library. This research was funded by Qatar University Internal Grant under Grant No. IRCC-2021–010.
Languageen
PublisherSpringer Nature
SubjectBig Data
Information system
TitleSystematic analysis of healthcare big data analytics for efficient care and disease diagnosing
TypeArticle
Issue Number1
Volume Number12
dc.accessType Open Access


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