Table 3 Description of dataset features.
From: Revolutionizing heart disease prediction with quantum-enhanced machine learning
Type | Name | Description | Range |
|---|---|---|---|
Demographic | Age | Patient’s age in years | 28 to 77 |
Demographic | Sex | Patient’s gender; 1-male; 0-female | 0 or 1 |
Symptom and examination | Chest pain type | 1-typical; 2-typical angina; 3-non anginal pain; 4-asymtomatic | 1 to 4 |
Symptom and examination | Resting blood pressure | Level of blood pressure at resting mode in mm/Hg | 0 to 200 |
Laboratory and echo | Cholesterol | Serum cholesterol in mg/dl | 0 to 603 |
Laboratory and echo | Fasting blood sugar | Blood sugar level on fasting > 120 mg/dl; 0-no; 1-yes | 0 to 1 |
ECG | Resting ECG | Result of ECG at rest; 0-normal; 1-ST-T wave abnormality; 2-showing probable or definite left ventricular hypertrophy by Estes’ criteria | 0 to 2 |
ECG | Maximum heart rate | Maximum heart rate achieved | 60 to 202 |
Symptom and examination | Exercise angina | Angina induced by exercise; 0-no; 1-yes | 0 to 1 |
ECG | Old peak | Exercise-induced ST depression in comparison with the state of rest | -2.6 to 6.2 |
ECG | ST slope | The slope of the peak exercise ST segment; 1-up sloping; 2-flat; 3-down sloping | 0 to 3 |
Target variable | 0-normal; 1-HD (heart disease) | 0 or 1 | |
