Diabetes-focused food recommender system (DFRS) to enabling digital health

Esmael Ahmed, Mohammed Oumer and Medina Hassan

PLOS Digital Health, 2025, vol. 4, issue 2, 1-10

Abstract: The integration of digital health technologies into diabetes management has shown the potential to improve patient outcomes by providing personalized dietary recommendations. This study aims to develop and evaluate the Diabetes-Focused Food Recommender System (DFRS), a system designed to assist individuals with diabetes in making informed food choices. Using a combination of advanced machine learning algorithms, nutrition science, and digital health technologies, DFRS generates personalized recommendations tailored to individual needs. The methodology involves data collection from diverse patient profiles and model development using Graph Neural Networks (GNN) and other machine learning techniques. Hyperparameter tuning and rigorous performance evaluation were conducted to optimize system accuracy. The results demonstrate that after optimization, GNN achieved an accuracy of 94 percent, significantly enhancing the precision of dietary recommendations. Clinical validation of the system showed a reduction in HbA1c levels, glycemic variability, and incidents of hyper- and hypoglycemia. Therefore, DFRS has proven to be an effective tool for improving dietary management in diabetes care, and its integration into clinical workflows offers the potential to enhance health outcomes and streamline healthcare delivery.Author summary: In this research, we introduce the Diabetes-Focused Food Recommender System (DFRS), a digital health solution aimed at improving dietary management for individuals with diabetes. This study responds to the challenges diabetes patients face in making informed dietary choices due to the overwhelming amount of information and personal variability. By leveraging advanced machine learning algorithms alongside nutrition science, DFRS provides personalized dietary recommendations tailored to individual needs. Our development process included rigorous optimization to ensure the system’s adaptability and effectiveness within clinical settings. We found that DFRS significantly enhances glycemic control and reduces diabetes-related complications. Continuous feedback from healthcare professionals and patients informed its refinement, ensuring it meets the needs of real-world users. DFRS is a notable advancement in personalized medicine, empowering users to make informed dietary decisions that can lead to improved health outcomes. Through sustained innovation, DFRS has the potential to transform dietary management and enhance the quality of life for individuals living with chronic conditions like diabetes.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pdig00:0000530

DOI: 10.1371/journal.pdig.0000530

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