Awesome Heart Sound Analysis - A Survey

A Machine Learning model that predicts the occurrence of prevalent Stroke, Hypertension, Coronary Heart Disease and Diabetes using Framingham's dataset.

A Machine Learning project for Cardiovascular disease prediction

Supervised ML - Classification Using Python this project demonstrates the effectiveness of machine learning techniques in predicting cardiovascular risk using the Framingham Heart Study dataset. The developed machine learning model can be used by healthcare professionals to identify individuals at high risk of cardiovascular disease .

Projet d'analyse de données - Maladies cardiovasculaires- R

This repo contains a Machine Learning-based methodology for the preliminary design of a risk calculator using medical tabular databases, combining the knowledge of different clinically validated cardiovascular risk calculators using Transfer Learning (TL).

Developpement of a machine learning model (SVM classifier) for cardiovascular disease prediction. Deployed on a streamlit app.

Ensemble Learning

It is a Capstone project. A model has been created to predict for the heart diseases. It can be very useful for the health sector as cardiovascular diseases are rapidly increasing. The record contains patients' information. It includes over 4,000 records and 15 attributes.

Welcome to the Cardiovascular Disease Prediction Project! 💖❤️‍🔥 Cardiovascular disease (CVD) remains a global health challenge, accounting for significant morbidity and mortality rates worldwide. In response, I have developed an innovative deep learning model designed to predict CVD leveraging ANNs and CNNs.

Machine Learning based Cardiovascular Disease Detection

Public repository associated with: Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs

Automatic ECG classification using discrete wavelet transform and one-dimensional convolutional neural network

Blake's Haas Capstone Project - Patient Readmissions Prediction

INVESTIGATING THE ASSOCIATION BETWEEN POLYGENIC RISK SCORE OF ADIPOSE TISSUE FUNCTION AND CARDIOVASCULAR DISEASE

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

Proyecto que busca predecir enfermedades cardiovasculares en pacientes potenciales, analizando una serie de factores de la salud cardiaca de los mismos, a partir de la ayuda de machine learning vía tres clasificadores de aprendizaje supervisado.

Detecting Heart disease in patients using svm