Journal of Computer Technology & Applications

Journal of Computer Technology & Applications Original Research

Fuzzy Logic Driven Nutrition-based Recommendation System for Gujarati Cardiac Patients: Integrating Cultural Preferences and Patient Feedback

  1. Nirav Mehta Department of Computer Science, Shri V. J. Modha College, Porbandar

Abstract

This article focuses on developing a comprehensive dataset for accurate dietary recommendations tailored to Gujarati cardiac patients' needs. The dataset comprises nutritional details of over 90 Gujarati food and fruit products, meticulously collected through primary and secondary data collection methods. Each food item's nutritive values, including proteins, carbohydrates, fats, fiber, and calories, are meticulously recorded to facilitate precise dietary recommendations. The dataset integrates cultural preferences and seasonal variations in food availability to ensure relevance and adherence to dietary guidelines. Additionally, the research incorporates feedback from cardiac patients, who rate food preferences on a scale of 1 to 10, enhancing the dataset's accuracy and relevance. By leveraging this rich dataset, the research aims to develop an effective recommendation system that provides personalized and culturally sensitive dietary guidance to improve the cardiac health management of Gujarati patients.

Keywords

  • Cardiac patients
  • FUZZY LOGIC
  • Gujarati cuisine
  • Nutrition-based recommendation system
  • cultural preferences
  • dataset
  • dietary management
  • feedback integration
  • nutritive values
  • personalized recommendations

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