Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Healthcare Analytics: Conceptualizing a Research Agenda
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.ORCID iD: 0000-0003-4250-4752
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.ORCID iD: 0000-0001-5637-9572
2024 (English)In: Procedia Computer Science / [ed] Ricardo Filipe Gonçalves Martinho; Maria Manuela Cruz da Cunha, Elsevier, 2024, Vol. 239, p. 1678-1686Conference paper, Published paper (Refereed)
Abstract [en]

This research recognizes the pressing need for innovative research in healthcare, enabling the transition towards analytics, by explaining how previous studies utilized big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods are combined with contemporary data science techniques to understand the literature, identify research gaps, and posit research questions for researchers, academic institutions, and governmental healthcare organizations. We intend to explain how contemporary analytics have been used to address healthcare concerns as well as to posit several research questions for future studies based on gaps which we have identified. The study has multi-folds contribution areas: first, it provides a state-of-the-art review to healthcare analytics, second, it posits a research agenda to advance the knowledge in this area further.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 239, p. 1678-1686
Keywords [en]
healthcare, data science, data analytics, AI, big data, machine learning
National Category
Information Systems, Social aspects
Research subject
Information Systems
Identifiers
URN: urn:nbn:se:ltu:diva-108953DOI: 10.1016/j.procs.2024.06.345Scopus ID: 2-s2.0-85201280518OAI: oai:DiVA.org:ltu-108953DiVA, id: diva2:1892344
Conference
CENTERIS – International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2023, Porto, Portugal, November 8-10, 2023
Note

Fulltext license: CC BY-NC-ND

Available from: 2024-08-26 Created: 2024-08-26 Last updated: 2024-11-26Bibliographically approved

Open Access in DiVA

fulltext(563 kB)87 downloads
File information
File name FULLTEXT01.pdfFile size 563 kBChecksum SHA-512
ea0d1b378292ed2f3b65ed713d711d85adb29cb23c2e40f9a89668c3b4a820be01a48185a64edc23a6f8a67b79abac4ddb22dd3010d27dce06802ebc4466a18f
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Elragal, Rawan A.Elragal, AhmedHabibipour, Abdolrasoul

Search in DiVA

By author/editor
Elragal, Rawan A.Elragal, AhmedHabibipour, Abdolrasoul
By organisation
Digital Services and Systems
Information Systems, Social aspects

Search outside of DiVA

GoogleGoogle Scholar
Total: 87 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 454 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf