Table 2 Data attributes description.

From: A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques

S. No.

Feature

Description

1.

Age

Age of the patient [years]

2.

Sex

Sex of the patient [M: Male, F: Female]

3.

Chest Pain Type

Chest pain type [TA: Typical Angina, ATA: Atypical Angina, NAP: Non-Anginal Pain, ASY: Asymptomatic]

4.

Resting BP

Resting blood pressure [mm Hg]

5.

Cholesterol

Serum cholesterol [mm/dl]

6.

Fasting BS

Fasting blood sugar [1: if FastingBS > 120 mg/dl, 0: otherwise]

7.

Resting ECG

Resting electrocardiogram results [Normal: Normal, ST: having ST-T wave abnormality, LVH: probable or definite LVH]

8.

Max HR

Maximum heart rate achieved [Numeric value between 60 and 202]

9.

Exercise Angina

Exercise-induced angina [Y: Yes, N: No]

10.

Oldpeak

ST [Numeric value measured in depression]

11.

ST_Slope

The slope of the peak exercise ST segment [Up: upsloping, Flat: flat, Down: downsloping]

12.

Heart Disease

Output class [1: heart disease, 0: Normal]