This repository contains the three-part capstone project made for the DTU Data Science course 02450: Introduction to Machine Learning and Data Mining

This web application is motivated by Baymax of the animated movie Big Hero 6. It detects Valvular Heart disorder i.e. damage or defect in one of the four heart valves. On the Machine Learning side, I have used AutoML from the deep learning platform H2O. And the interactive application is build in RShiny.

This program classifies a person depending on the data, whether he is having cardiovuscular disease or not. The dataset is also included in the dataset.

Final year capstone project for heart disease detection using a multi-modal approach. We trained separate ML models on ECG, PCG, and PPG signals and fused their confidence scores using a mathematical method to provide a more accurate and holistic risk assessment.

In this project I have created an Heart Diseases predictive model that can accurately predicts whether a person has heart disease or not based on some medical data.

A PyTorch model with a 99.27% accuracy designed to predict the risk of heart disease based on a combination of symptoms, lifestyle factors, and medical history from 70,000+ data samples.

KNN Core for Heart Disease Diagnosis in C++

Some mini projects and code for machine learning application