[Retracted] Implementation of a Heart Disease Risk Prediction Model Using Machine Learning

Table 1

UCI ML repository’s Cleveland heart disease dataset—feature subset [24].

Attribute name	Attribute description
Age	Age in years
Sex	1 denotes male and 0 denotes female
CP	Chest pain type 1, typical angina; type 2, atypical angina; type 3, nonanginal pain; and type 4, asymptomatic
trestbps	Resting blood pressure (in mmHg at entry to the health center)
chol	Serum lipid level in mg/dL
fbs	1 denotes true, i.e., the fasting blood sugar  mg/dL; 0 denotes false
restecg	Resting ECG results: null, normal; 1, ST-T wave abnormality; and 2, probable or definite left ventricular hypertrophy
thalach	Maximum heart rate achieved
exang	Exercise induced angina (; )
oldpeak	ST depression induced by exercise relative to rest
slope	The slope of the peak exercise ST segment (1, 2, and 3): 1, upsloping; 2, flat; and 3, downsloping
ca	Number of major vessels (0-3) colored by fluoroscopy
thal	Thalassemia: , , and