Towards a Health Recommender Tool using Machine Learning Approaches: A survey and a new idea

A sanitary crisis is a series of health events that can affect a large number of persons. Late events (COVID 19) have shown how unprepared we are to such situations. This issue raises the need to propose a Health Recommender Tool (HRT) to help both patients and medical professionals make more efficient and accurate health-related decisions. This paper presents an overview of recommendation systems (RS) methods that can be classified into categories: content-based method, collaborative filtering and hybrid method. We provide a literature review on machine learning (ML) based RS mainly in the medical domain. This work proposes a multi-phase process where the first phase is the data pre-processing and the second is the use of ML based recommendation techniques to get predictions on the relevance of documents to the user. The last step is the comparison between each technique. Our study concerns especially Algeria where the need of this kind of tools is greatest.