Defining architectures for recommended systems for medical treatment. A Systematic Literature Review

Cristina Jimenez; Ivan Carrera

Cristina Jimenez Escuela Politécnica Nacional
Ivan Carrera Escuela Politécnica Nacional

Keywords: Recommender System, Machine Learning, Assisted Medicine.

Abstract

This paper presents a Systematic Literature Review(SLR) related to recommender system for medical treatment, aswell as analyze main elements that may provide flexible, accurate,and comprehensive recommendations. To do so, a SLR researchmethodology obey. As a result, 12 intelligent recommendersystems related to prescribing medication were classed dependingto specific criteria. We assessed and analyze these medicinerecommender systems and enumerate the challenges. After studyingselected papers, our study concentrated on two researchquestions concerning the availability of medicine recommendersystems for physicians and the features these systems should have.Further research is encouraged in order to build an intelligentrecommender system based on the features analyzed in this work.

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Author Biography

Cristina Jimenez, Escuela Politécnica Nacional

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