Early detection of Coronary Heart Disease by using Naive Bayes Algorithm

Author:

Krithiga B.,Sabari P.,Jayasri I.,Anjali I.

Abstract

Abstract In smart connected communities, Health monitoring devices are vital parts of smart health. The main goal of this project is to detect the mild abnormalities of the coronary heart disease in the initial stage by providing quality health care using Naive Bayes classifier. The Coronary heart disease is diagnosed by taking into consideration the parameters like age, gender, nature of chest pain, latent blood pressure, serum cholesterol level, fasting blood sugar level, resting ECG, maximum heart rate, exercise induced angina, ST depression induced, peak exercise ST, number of major vessels and thalassemia. These parameters are used in the classifier to examine whether the Coronary heart disease is present or absent along with its accurateness.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comparison of shallow and deep learning methods of ECG signals clas-sification for arrhythmia detection;Journal of Computer Sciences Institute;2023-06-30

2. Cardiac Disease Prediction using Artificial Intelligence;2023 Advances in Science and Engineering Technology International Conferences (ASET);2023-02-20

3. Early Stage Detection of Cardiac Related Diseases by Using Artificial Neural Network;Recent Advances in Soft Computing and Data Mining;2022

4. Wearable Sensor Signals: An Overview of the AI Models Most Commonly Applied to Time Series Data Analysis;Connected e-Health;2022

5. Machine Learning Techniques and Computing Technologies for IoT based Smart Healthcare (COVID-19 Case Study);2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2021-12-17

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