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Latest Trends in Recommender Systems applied in the medical domain: A Systematic Review - 2020

Latest Trends In Recommender Systems Applied In The Medical Domain: A Systematic Review

Research Area:  Machine Learning

Abstract:

Recommender systems use algorithms to provide users with product or service recommendations. In recent times, these systems have been using Artificial Intelligence algorithms. However, choosing a suitable AI algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using AI algorithms often faces problems and raises questions that must be resolved. In this context developing recommender system in the medical domain are presented as complementary tools in decision-making processes in healthcare services, it allows to increase the usability of technologies and reduce information overload in processes. This paper presents a systematic review of the literature that analyze the use of AI algorithms in recommender system and identify new research opportunities. The goals of this study are to (i) identify latest trends in the use or research of AI algorithms in recommender system applied in the medical domain;(ii)identify open questions in the use or research of AI algorithms, and (iii)assist new researchers to position new research activity in this domain appropriately.

Keywords:  

Author(s) Name:  Stitini Oumaima , Kaloun Soulaimane , Bencharef Omar

Journal name:  

Conferrence name:  NISS2020: Proceedings of the 3rd International Conference on Networking, Information Systems & Security

Publisher name:  ACM

DOI:  10.1145/3386723.3387860

Volume Information:  March 2020, Article No.: 41,Pages 1–12