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Towards Health (Aware) Recommender Systems
Technische Universität München.
University of Seville.
University of Minnesota.
RWTH Aachen.
Show others and affiliations
2017 (English)In: 2017 ACM Conference on Digital Health (DH'17), London: Association for Computing Machinery (ACM), 2017Conference paper (Refereed)
Abstract [en]

People increasingly use the Internet for obtaining information regarding diseases, diagnoses and available treatments. Currently, many online health portals already provide non-personalized health information in the form of articles. However, it can be challenging to find information relevant to one’s condition, interpret this in context, and understand the medical terms and relationships. Recommender Systems (RS) already help these systems perform precise information filtering. In this short paper, we look one step ahead and show the progress made towards RS helping users find personalized, complex medical interventions or support them with preventive healthcare measures. We identify key challenges that need to be addressed for RS to offer the kind of decision support needed in high-risk domains like healthcare.

Place, publisher, year, edition, pages
London: Association for Computing Machinery (ACM), 2017.
Keyword [en]
recommender systems, user modelling, health informatics
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:his:diva-13551DOI: 10.1145/3079452.3079499OAI: oai:DiVA.org:his-13551DiVA: diva2:1094212
Conference
ACM 7th Digital Health, 2-5 July, 2017 London
Available from: 2017-05-09 Created: 2017-05-09 Last updated: 2017-05-09

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CiteExportLink to record
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