5. Diagnose Heart Disease

In this lab, you’re going to write an app in C# that detects heart disease for patients in a hospital in Cleveland. You’ll use the Cleveland CAD dataset, which has detailed medical data for a group of patients who visited the hospital suffering from chest pain. The data includes age and gender, pain type, blood test results and EKG data. All you need to build an accurate diagnostic tool.

Just like with the New York TLC dataset, you will have to analyze the dataset by generating a histogram grid, correlation matrix and scatterplot grid, and use the results to design and build a machine learning pipeline. You will perform feature engineering by detecting and dealing with outliers, normalizing columns, one-hot encoding categorical data columns, and adding new calculated features where applicable.

Finally, I’ll give you the medical data of a fictional patient and you can use the fully trained model to predict if they have heart disease or not.