ArticleScientific reports2023
A fuzzy based dietary clinical decision support system for patients with multiple chronic conditions (MCCs).
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- The Use of Artificial Intelligence (AI) to Support Dietetic Practice Across Primary Care: A Scoping Review of the Literature.Nutrients · 2025Article
- DHerbKB for CKD: knowledge base of diet and toxic herbal medicines for clinical support of chronic kidney disease.Journal of translational medicine · 2025Article
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3 authors.
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Abstract
Due to the multifaceted nature of Multiple Chronic Conditions (MCCs), setting a diet for these patients is complicated and time-consuming. In this study, a clinical decision support system based on fuzzy logic was modeled and evaluated to aid dietitians in adjusting the diet for patients with MCCs. Mamdani fuzzy logic with 1144 rules was applied to design the model for MCCs patients over 18 years who suffer from one or more chronic diseases, including obesity, diabetes, hypertension, hyperlipidemia, and kidney disease. One hundred nutrition records from three nutrition clinics were employed to measure the system's performance. The findings showed that the diet set by nutritionists had no statistically significant difference from the diet recommended by the fuzzy model (p > 0.05), and there was a strong correlation close to one between them. In addition, the results indicated a suitable model performance with an accuracy of about 97%. This system could adjust the diet with high accuracy as well as humans. In addition, it could increase dietitians' confidence, precision, and speed in setting the diet for MCCs patients.
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