An Extensive Dataset for the Heart Disease Classification System

Published: 17 February 2022| Version 2 | DOI: 10.17632/65gxgy2nmg.2
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Description

Finding a good data source is the first step toward creating a database. Cardiovascular illnesses (CVDs) are the major cause of death worldwide. CVDs include coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other heart and blood vessel problems. According to the World Health Organization, 17.9 million people die each year. Heart attacks and strokes account for more than four out of every five CVD deaths, with one-third of these deaths occurring before the age of 70. A comprehensive database for factors that contribute to a heart attack has been constructed. The main purpose here is to collect characteristics of Heart Attack or factors that contribute to it. The size of the dataset is 1319 samples, which have nine fields, where eight fields are for input fields and one field for an output field. Age, gender, heart rate (impulse), systolic BP (pressurehight), diastolic BP (pressurelow), blood sugar(glucose), CK-MB (kcm), and Test-Troponin (troponin) are representing the input fields, while the output field pertains to the presence of heart attack (class), which is divided into two categories (negative and positive); negative refers to the absence of a heart attack, while positive refers to the presence of a heart attack.

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Institutions

Erbil Polytechnic University, University of Kurdistan Hewler

Categories

Health Informatics, Machine Learning, Health Care

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