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2020 | OriginalPaper | Chapter

A Fuzzy Logic Based Cardiovascular Disease Risk Level Prediction System in Correlation to Diabetes and Smoking

Authors : Kanak Saxena, Umesh Banodha

Published in: Data Management, Analytics and Innovation

Publisher: Springer Singapore

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Abstract

The cardiovascular disease (CVD) is one of the major causes of death among the people having diabetes in addition to smoking habits. It will create tribulations for every organ of the human body. Smoking becomes fashion among the youth from their childhood which results in premature death. The intention of this paper is to explain the impact of diabetes and smoking along with high BP, high pulse rate, angina affect, and family history on the CVD risk level. The concept used is based on the knowledge-based system. We have proposed a fuzzy-logic-based prediction system to evaluate the CVD risk among the people having diabetes with smoking habits. The aim is to facilitate the experts to provide the medication as well as counsel the smokers well in advance. This will not merely save the individual but also an immense relief to concern. The data set is used from UCI (Machine Learning Repository). Most of the researchers worked on diabetes or smoking impact on CVD separately, but the proposed system demonstrates how drastically it will affect ones’ health condition.

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Metadata
Title
A Fuzzy Logic Based Cardiovascular Disease Risk Level Prediction System in Correlation to Diabetes and Smoking
Authors
Kanak Saxena
Umesh Banodha
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-32-9949-8_3