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An Approach for Developing Diabetes Prediction and Recommendation System

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Authors:
Saima Sultana, Abdullah Al Momen, Mohoshi Haque, Mahmudul Hasan Khandaker, Nazmus Sakib
10.5120/ijca2021921033

Saima Sultana, Abdullah Al Momen, Mohoshi Haque, Mahmudul Hasan Khandaker and Nazmus Sakib. An Approach for Developing Diabetes Prediction and Recommendation System. International Journal of Computer Applications 174(14):20-28, January 2021. BibTeX

@article{10.5120/ijca2021921033,
	author = {Saima Sultana and Abdullah Al Momen and Mohoshi Haque and Mahmudul Hasan Khandaker and Nazmus Sakib},
	title = {An Approach for Developing Diabetes Prediction and Recommendation System},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2021},
	volume = {174},
	number = {14},
	month = {Jan},
	year = {2021},
	issn = {0975-8887},
	pages = {20-28},
	numpages = {9},
	url = {http://www.ijcaonline.org/archives/volume174/number14/31746-2021921033},
	doi = {10.5120/ijca2021921033},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Diabetes is a severe, enduring disorder with a huge impact on the existence and health of individuals and the people around them. It happens due to insufficient production of insulin in human body. After investigating the dangers of diabetes, it can be said that diagnosing diabetes with basic medical information at early stage of diabetes can help patients to control it and also predicting the probability of having diabetes can really decrease the number of diabetic patients in future. So, for the prediction of this disease, Multiple Linear Regression (MLR) has been used. To implement this model, some basic medical information of a person have been used as parameters. 83% accuracy has been achieved using this model. A set of suggestions using the Reinforcement Learning also have been generated to help the diabetic patients to control this disease.

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Keywords

Diabetes Mellitus, Prediction System, Recommendation System, Multiple Linear Regression (MLR), Simple Linear Regression, Age, Body Mass Index (BMI), Blood Pressure, Blood Sugar, Exercise Time and Sleeping Time.