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Table 1 Description of variables UCI heart dataset

From: Machine learning-based identification of patients with a cardiovascular defect

Variable Description
Age Age in years (29 to 77)
Sex Gender instance (0 = Female, 1 = Male)
ChestPainType Chest pain type (1: typical angina, 2: atypical angina, 3: non- anginal pain, 4: asymptomatic)
RestBloodPressure Resting blood pressure in mm Hg[94, 200]
ChestPainType Serum cholesterol in mg/dl[126, 564]
FastingBloodSugar Fasting blood sugar> 120 mg/dl (0 = False, 1= True)
ResElectrocardiograp Resting ECG results (0: normal, 1: ST-T wave abnormality, 2: LV hypertrophy)
MaxHeartRate Maximum heart rate achieved[71,202]
ExerciseInduced Exercise-induced angina (0: No, 1: Yes)
Oldpeak ST depression induced by exercise relative to rest [0.0, 62.0]
Slope Slope of the peak exercise ST segment (1: up-sloping, 2: flat, 3: downsloping)
MajorVessels Number of major vessels colored by fluoroscopy (values 0 - 3)
Thal Defect types: value 3: normal, 6: fixed defect, 7: irreversible defect
HeartDisease Target : value 0: absence of disease, 1 or 2 or 3 or 4 or 5: presence of cardiovascular disease