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This paper presents a fuzzy logic-based personalized diet recommendation engine specifically designed for stroke-vulnerable patients using the Nigerian food composition table. The system utilizes a Mamdani fuzzy inference model to recommend diets based on seven stroke risk factors derived from user profiles, aiming to improve nutrient balance and reduce stroke risk. The engine was developed and tested using Python, demonstrating efficiency in providing tailored dietary suggestions to enhance health outcomes

Author

International Journal of Technology, Health and Sustainability

Language

EN