In this work we present a semantic recommender system able to suggest doctors and hospitals that best fit a specic patient prole. The recommender system is the core component of the social network named HealthNet (HN). The recommendation algorithm first computes similarities among patients, and then generates a ranked list of doctors and hospitals suitable for a given patient prole, by exploiting health data shared by the community. Accordingly, the HN user can find her most similar patients, look how they cured their diseases, and receive suggestions for solving her problem. Currently, the alpha version of HN is available only for Italian users, but in the next future we want to extend the platform to other languages. We organized three focus groups with patients, practitioners, and health organizations in order to obtain comments and suggestions. All of them proved to be very enthusiastic by using the HN platform1.
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|Titolo:||A Recommender System for Connecting Patients to the Right Doctors in the HealthNet Social Network|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||4.3 Poster|