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. 2023 Feb 27;20(5):4248.
doi: 10.3390/ijerph20054248.

A Systematic Review on Food Recommender Systems for Diabetic Patients

Raciel Yera  1   2 , Ahmad A Alzahrani  3 , Luis Martínez  1 , Rosa M Rodríguez  1
Affiliations

A Systematic Review on Food Recommender Systems for Diabetic Patients

Raciel Yera et al. Int J Environ Res Public Health. .

Abstract

Recommender systems are currently a relevant tool for facilitating access for online users, to information items in search spaces overloaded with possible options. With this goal in mind, they have been used in diverse domains such as e-commerce, e-learning, e-tourism, e-health, etc. Specifically, in the case of the e-health scenario, the computer science community has been focused on building recommender systems tools for supporting personalized nutrition by delivering user-tailored foods and menu recommendations, incorporating the health-aware dimension to a larger or lesser extent. However, it has been also identified the lack of a comprehensive analysis of the recent advances specifically focused on food recommendations for the domain of diabetic patients. This topic is particularly relevant, considering that in 2021 it was estimated that 537 million adults were living with diabetes, being unhealthy diets a major risk factor that leads to such an issue. This paper is centered on presenting a survey of food recommender systems for diabetic patients, supported by the PRISMA 2020 framework, and focused on characterizing the strengths and weaknesses of the research developed in this direction. The paper also introduces future directions that can be followed in the next future, for guaranteeing progress in this necessary research area.

Keywords: diabetes; food recommendation; nutritional information; user preferences.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flow of this paper.
Figure 2
Figure 2
Search process for supporting the systematic literature review.
Figure 3
Figure 3
Systematic flow diagram representing the inclusion of studies according to the PRISMA 2020 Declaration.
Figure 4
Figure 4
Relevant terms and their co-occurrence across the revised papers.
Figure 5
Figure 5
Overview of the data sources and recommendation methods identified at the survey.
See this image and copyright information in PMC

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