An Empirical Study and Analysis of Heart Disease Prediction

R Subhashini

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English

Oliver & Boyd
25 March 2023

Diseases & disorders; Cardiovascular medicine; Coping with illness

Summary
Details

An empirical study and analysis of heart disease prediction involves using data analysis techniques to identify patterns and risk factors associated with cardiovascular disease. This approach utilizes machine learning algorithms to classify patients based on their likelihood of developing heart disease.

The study involves collecting data on risk factors such as age, gender, family history, blood pressure, cholesterol levels, smoking, and diabetes. Feature selection techniques are used to identify the most important risk factors, and a classification model is trained using these factors. The accuracy of the model is evaluated using metrics such as sensitivity, specificity, and AUC.

This empirical study and analysis has several advantages, including the ability to identify new risk factors associated with heart disease, improved accuracy in predicting cardiovascular risk, and the potential to develop more personalized prevention and treatment strategies. This approach has the potential to improve medical decision-making and reduce the burden of heart disease on individuals and society.

By: R Subhashini
Imprint: Oliver & Boyd
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm, Spine: 5mm
Weight: 145g
ISBN: 9780056822436
ISBN 10: 005682243X
Pages: 100
Publication Date: 25 March 2023
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active