Health Recommender Systems: A State-of-the-Art Review

Abstract

The use of information technologies in the health domain started decades ago, nevertheless there are still many issues that need to be addressed. Health Recommender Systems (HRSs) constitute a promising alternative when it comes to providing tools to assist doctors in the diagnosis of diseases, as well as to help patients with recommendations in regards of how to keep their wellness. This work provides insights about methods and techniques used in the design and development of HRSs, focusing on the areas or types of the recommendations these systems provide and the data representations they employ to build their knowledge base. For this effect, a number of articles published between January 2006 and August 2018, from five different scientific databases, were retrieved. After an examination and selection of publications, 249 articles were categorized by means of a classification framework which was built upon related works and the content of the studies analyzed. Furthermore, the results of the classification are presented and major findings are outlined and discussed.