Do recommender systems function in the health domain: a system review

TL;DR

This systematic review examines the current state, challenges, and future directions of health recommender systems, highlighting their potential and limitations in supporting health-related decision-making.

Contribution

The paper provides a comprehensive review of health recommender systems, analyzing their methods, evaluation challenges, and future research directions.

Findings

Health recommender systems focus on low-risk recommendations like diet.

Knowledge-based methods outperform traditional collaborative filtering in health.

Evaluating health recommendations involves multiple complex metrics.

Abstract

Recommender systems have fulfilled an important role in everyday life. Recommendations such as news by Google, videos by Netflix, goods by e-commerce providers, etc. have heavily changed everyones lifestyle. Health domains contain similar decision-making problems such as what to eat, how to exercise, and what is the proper medicine for a patient. Recently, studies focused on recommender systems to solve health problems have attracted attention. In this paper, we review aspects of health recommender systems including interests, methods, evaluation, future challenges and trend issues. We find that 1) health recommender systems have their own health concern limitations that cause them to focus on less-risky recommendations such as diet recommendation; 2) traditional recommender methods such as content-based and collaborative filtering methods can hardly handle health constraints, but knowledge-based methods function more than ever; 3) evaluating a health recommendation is more complicated than evaluating a commercial one because multiple dimensions in addition to accuracy should be considered. Recommender systems can function well in the health domain after the solution of several key problems. Our work is a systematic review of health recommender system studies, we show current conditions and future directions. It is believed that this review will help domain researchers and promote health recommender systems to the next step.