Fuzzy Nutrition Recommendation System for Diabetic Patients

  • Aryaman Gupta
  • Sanjay Kumar Dubey
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 624)


Till 2013, the total number of patients suffering from Diabetes Mellitus reached a total of 382 Million. There is a significant growth from 4.7% in 1980 to 8.5% in 2014 as per the World health organization. Diabetes is not a new word to world now days. It has become a major health problem irrespective of the age group the people belong to. Not just it, most of the times Diabetes is accompanied with other ailments like Hypertension, blood pressure etc. All the researchers, Doctors and Practitioners have a unanimous accord to one fact that Diet plays the most significant role in the cause as well as curb of diabetes. All the fuzzy systems developed so far have given a suitable diet recommendation system or a system for detection and Diagnosis of diabetes. Citing the role of diet to curb the harmful effects of diabetes in the patients, there was a need to come up with a Fuzzy diet recommendation system which is specific to the Diabetes and the diabetic patients and not a diet recommendation system in general. Essentially, the diet of a healthy person should be a lot different from the one suffering from diabetes. The paper uses fuzzy logic to analyze to present a suitable diet recommendation system for the patients suffering from Diabetes.


Fuzzy logic Nutrition Diabetes System TSK model 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAmity University Uttar PradeshNoidaIndia

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