Heart attack analysis

This is a data mining project for the data mining course of the Data Science University of Florence.

We will use the Heart attack dataset named heart.csv to predict an heart attack.

It's suggested to run the Jupyter notebook in a virtual environment and use the following command to install the dependencies needed for the project.

pip install -r requirements.txt

Here there is a description of the values in the dataset.

1. age - age in years

2. sex - sex (1 = male; 0 = female)

3. cp - chest pain type (0 = asymptomatic, 1 = typical angina; 2 = atypical angina; 3 = non-anginal pain)

4. trtbps - resting blood pressure (in mm Hg on admission to the hospital)

5. chol - serum cholesterol in mg/dl

6. fbs - fasting blood sugar > 120 mg/dl (1 = true; 0 = false)

7. restecg - resting electrocardiographic results (1 = normal; 2 = having ST-T wave abnormality; 0 = hypertrophy)

8. thalachh - maximum heart rate achieved

9. exng - exercise induced angina (1 = yes; 0 = no)

10. oldpeak - ST depression induced by exercise relative to rest (measured in millimeters)

11. slp - the Slope of ST segment at peak exercise (0 = downsloping; 1 = flat/horizontal; 2 = upsloping;)

12. caa - number of major vessels (0-4) colored by fluoroscopy

13. thall - 1 = fixed defect; 2 = normal; 3 = reversible defect

14. output - diagnosis of heart disease (angiography disease status) (0 = diameter narrowing, 1 = more than 50% diameter narrowing)

Definitions for understanding the dataset description

Angiography or arteriography is a medical imaging technique used to visualize the inside of blood vessels and organs of the body, with particular interest in the arteries, veins, and the heart chambers.

Coronary angiography can visualize coronary artery stenosis which is an abnormal narrowing in a blood vessel.

An abnormal diameter narrowing of more than 50% is associated with a very high risk of heart attack, which is what we want to predict

Angina is a type of chest pain caused by reduced blood flow to the heart and it is a symptom of coronary artery disease.

ST depression refers to a finding on an electrocardiogram, wherein the trace in the ST segment is abnormally low below the baseline.

Slope of ST segment at peak exercise could be:

1. Horizontal slope is very typical of ischemia.

2. Downsloping is typical of ischemia.

3. Upsloping of ST segment depression is a normal finding during physical exercise, and it should be considered normal if the T-waves are not inverted. Hyperventilation, however may cause similar ST segment depression.

Nuclear stress testing requires the injection of a tracer, commonly technicium 99M (Myoview or Cardiolyte), which is then taken up by healthy, viable myocardial cells.

A camera (detector) is used afterwards to image the heart and compare segments

A coronary stenosis is detected when a myocardial segment takes up the nuclear tracer at rest, but not during cardiac stress. This is called a reversible defect.

Scarred myocardium from prior infarct will not take up tracer at all and is referred to as a fixed defect.

TO DO:

• Create the repository on GitHub
• Upload the dataset, README.md and .gitignore
• Provide the used Python libraries
• Inspect the dataset and make some pre-processing (if needed)
• Visualize the dataset and save the pictures in the Pictures folder
• Split the dataset in training set e test set
• Apply Decision Tree
• Apply KNN
• Apply Naive Bayes
• Compare accuracy and precision of the models above

This project is made by Ernesto Palchetti and Christian Mancini