Towards Health (Aware) Recommender Systems
Hanna Schäfer (Technische Universität München)
Santiago Hors-Fraile (University of Seville)
Raghav Pavan Karumur (University of Minnesota Twin Cities)
André Calero Valdez (RWTH Aachen University)
Alan Said (University of Skövde)
Helma Torkamaan (Universität Duisburg-Essen)
Tom Ulmer (University of St. Gallen)
Christoph Trattner (MODUL University Vienna)
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Abstract
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.
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