makrez/cardio_train

Short machine learning project

CAS AML Unibe - Module 1 & 2 Project¶

Analysis of Cardiovascular Disease

Group:

• Asad bin Imtiaz
• Hop Nguyen
• Marco Kreuzer

Introduction

In this project we aimed to find a way to predict the Cardiovascular Disease (CVD) using medical and demographoic features from around 70,000 patients. Cardiovascular disease (CVD) is a general term for conditions diseases that affect heart and blood vessels. CVD is a leading cause of death and disability in Swizerland and around the world, but a large part of can be prevented by maintaining a healthy lifestyle.

According to the latest WHO data published in 2020 Coronary Heart Disease Deaths in Switzerland reached 10,713 or 18.49% of total deaths. The age adjusted Death Rate is 41.51 per 100,000 of population ranks Switzerland #170 in the world. Cardiovascular disease and cancer are two of most widespread causes of death in Switzerland.

Several machine learning (ML) algorithms are increasingly being used to predict cardiovascular disease. We attempted here to build ML models to pridict the disease using a few common demographical and medical features with high accuracy. We employed several Unsumervised and Supervise approaches to predict the disease with high accuracy

Dataset

This dataset is openly accessible and was downloaded from Kaggle.

The link to data is: https://www.kaggle.com/datasets/sulianova/cardiovascular-disease-dataset