Smart collaboration framework for managing chronic disease using recommender system

Asmaa S Hussein, Wail M Omar, Xue Li and Muhammed Amer Hatem

Health Systems, 2014, vol. 3, issue 1, 12-17

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.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1057/hs.2013.8 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:thssxx:v:3:y:2014:i:1:p:12-17

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/thss20

DOI: 10.1057/hs.2013.8

Access Statistics for this article

Health Systems is currently edited by Sally Brailsford

More articles in Health Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().