Open Access

ARTICLE

Intelligent Nutrition Diet Recommender System for Diabetic’s Patients

Nadia Tabassum¹, Abdul Rehman², Muhammad Hamid^3,*, Muhammad Saleem⁴, Saadia Malik⁵, Tahir Alyas²

1 Department of Computer Science, Virtual University of Pakistan, Lahore, 54000, Pakistan
2 Department of Computer Science, Lahore Garrison University, Lahore, 54000, Pakistan
3 Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
4 Department of Industrial Engineering, Faculty of Engineering, Rabigh, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
5 Department of Information Systems, Faculty of Computing and Information Technology – Rabigh, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

* Corresponding Author: Muhammad Hamid. Email:

Intelligent Automation & Soft Computing 2021, 30(1), 319-335. https://doi.org/10.32604/iasc.2021.018870

Received 24 March 2021; Accepted 02 May 2021; Issue published 26 July 2021

Abstract

Diabetes is one of the ever-increasing menace crippling millions of people worldwide. It is an independent risk factor for many cardiovascular diseases including medium and small vessels and results in heart attack, stroke, kidney failure, blindness, and lower-limb amputations. According to a World Health Organization (WHO) report estimated 1.6 million deaths were the direct result of diabetes. Nutrition plays a vital role in diabetes management alongside physical activity, drugs, and insulin. Weight management can help to avert or delay at pre-diabetic stages. This research work explains the features of the Nutrition Diet Expert System (NDES), which will preferably be used by the health care professionals (HCPs) for calculating per day calorie requirements of diabetic patients and recommend the best diet plan to control diabetes. The primary objective of this proposed model for diet plan is to help individuals attain healthy body weight and optimum check on diabetes by gaining control over blood pressure and lipid count. The ultimate focus of this research result is prevention of diabetes related complications using nutrition diet expert system. In this paper, proposed recommender system has come in handy in figuring out the diet plan by determining the individual dietary requirements at the level of micro and macro nutrients for expert system using fuzzy logic. The results are very promising indicating testing and assessment of the expert system worked well for the individual diet plan.

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