Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/2057
Title: Design And Development Of Decision Support System To Recommend Nutritious Food For Cardiovascular Patients
Authors: Mehta, Nirav Pareshkumar
Thaker, Hetal
Keywords: CVDs
NBRS
Issue Date: Nov-2024
Publisher: Department of Computer Science, Faculty of Science Atmiya University
Citation: Mehta, N. P., Thaker, H. (2024). Design And Development Of Decision Support System To Recommend Nutritious Food For Cardiovascular Patients. Department of Computer Science, Faculty of Science Atmiya University
Abstract: Cardiovascular diseases (CVDs) are among the leading causes of mortality worldwide, and their prevalence is rapidly increasing in the Gujarat region of India. A major factor in managing cardiovascular health is adhering to a heart-healthy diet, which often presents challenges for patients in balancing nutritional needs with personal food preferences. To address this issue, this research introduces a *Nutrition-Based Recommendation System (NBRS)* aimed at providing personalized dietary guidance for individuals with heart-related problems. The NBRS leverages machine learning techniques to generate food recommendations that are not only nutritious but also aligned with individual tastes, daily calorie requirements, and cultural contexts, specifically focusing on the dietary habits of Gujarat. The foundation of this research lies in a thorough analysis of both primary and secondary data sources. Primary data was collected using a detailed questionnaire distributed to individuals with cardiovascular conditions. This questionnaire sought to capture their dietary habits, preferences, and ratings for various food items on a scale from 1 to 10. A dataset of over 90 distinct foods was compiled, each categorized into 15 groups such as fruits, vegetables, staple meals, and specific regional dishes like roti, bhakhri, thepla, dal, and rice. For each food item, nutritional parameters including fat, fiber, protein, carbohydrates, serving size, and calorie content were meticulously recorded. The secondary data included established nutritional guidelines for cardiac patients, emphasizing foods with high fiber and low fat. By integrating these insights, the dataset was structured to facilitate effective analysis and recommendation generation. A significant aspect of this model is its focus on *seasonal availability* of foods, ensuring that recommendations are practical and accessible. For instance, fruits like mangoes and apples were included, but their suggestions were aligned with their seasonal production to enhance freshness and nutritional value. This seasonal consideration allows the NBRS to remain relevant and adaptive throughout the year, providing users with timely options that are both heart-healthy and regionally appropriate.
URI: http://10.9.150.37:8080/dspace//handle/atmiyauni/2057
Appears in Collections:01. PhD. Thesis Computer Applications

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01_Title.pdf142.34 kBAdobe PDFView/Open
02_Prelim pages.pdf553.17 kBAdobe PDFView/Open
03_Contents.pdf105.1 kBAdobe PDFView/Open
04_Abstract.pdf7.35 kBAdobe PDFView/Open
05_Chapter 1.pdf619.89 kBAdobe PDFView/Open
06_Chapter 2.pdf254.52 kBAdobe PDFView/Open
07_Chapter 3.pdf103.46 kBAdobe PDFView/Open
08_Chapter 4.pdf3.01 MBAdobe PDFView/Open
09_Chapter 5.pdf1.08 MBAdobe PDFView/Open
10_Chapter 6.pdf186.84 kBAdobe PDFView/Open
11_Annexures.pdf130.24 kBAdobe PDFView/Open
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