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Smart collaboration framework for managing chronic disease using recommender system

Author

Listed:
  • Asmaa S Hussein
  • Wail M Omar
  • Xue Li
  • Muhammed Amer Hatem

Abstract

E-Healthcare services show promising solutions to reduce patients’ life risk with improving the provided services along with being cost effective. This paper presents Chronic Disease Recommender System that assists patients to monitor and control their cases through suggesting medical advices and diagnosis. For the system to be accurate, which is vital in such application, it needs to work with high-dimensional data. This work proposed Integrated Collaborative Filtering framework that reduces the complexity and improves the response time of high-dimensional data to develop recommender system. The paper concluded with presenting and discussing real case study with real medical data on providing medical advices for diabetes.

Suggested Citation

  • Asmaa S Hussein & Wail M Omar & Xue Li & Muhammed Amer Hatem, 2014. "Smart collaboration framework for managing chronic disease using recommender system," Health Systems, Taylor & Francis Journals, vol. 3(1), pages 12-17, February.
    • Handle: RePEc:taf:thssxx:v:3:y:2014:i:1:p:12-17
    DOI: 10.1057/hs.2013.8
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    Cited by:

    1. Shahnawaz Ahmad & Mohd. Aquib Ansari & Mohd. Arif & Javed Ahmad & Shabana Mehfuz & Justin Onyarin Ogala & O. S. Adewale, 2026. "Hybrid recommender system for personalized healthcare: integration of content-based and collaborative filtering approaches," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 17(1), pages 192-202, January.

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