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.
Keyword
Nutrition-based recommendation system, fuzzy logic, Gujarati cuisine, cardiac patients, dietary management, cultural preferences, personalized recommendations, nutritive values, dataset, feedback integration
Introduction
Cardiovascular diseases (CVDs) remain a significant health concern globally, with a substantial burden on populations worldwide. In regions like Gujarat, India, where cultural dietary preferences play a pivotal role in daily food choices, effective management of CVDs requires personalized dietary recommendations tailored to the local context. This paper presents a novel approach to addressing this challenge by developing a fuzzy logic-driven nutrition-based recommendation system (NBRS) for Gujarati cardiac patients.