Popular GitHub Repositories for Heart

Speech to Text to Speech. Song now playing. Sends text as OSC messages to VRChat to display on avatar. (STTTS) (Speech to TTS) (VRC STT System) (VTuber TTS)

It is a medical chatbot that will provide quick answers to FAQs by setting up rule-based keyword chatbots.

Remote heart rate detection through Eulerian magnification of face videos

ECG classification programs based on ML/DL methods

A Machine Learning and Deep Learning based webapp used to predict multiple diseases.

Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.

Using the SWELL dataset from Kaggle, we've built 2 machine learning models to predict whether or not a person is under stress using Heart Rate Variability(HRV) which can be collected from modern wearables such as fitbit devices and apple watches.

End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation. A replication of the RhythmNet model.

Intelligent Driver Monitoring system for Autonomous Vehicles

Stress classifier with AutoML

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.

This project will focus on predicting heart disease using neural networks. Based on attributes such as blood pressure, cholestoral levels, heart rate, and other characteristic attributes, patients will be classified according to varying degrees of coronary artery disease

Interpretable Pre-Trained Transformers for Heart Time-Series Data

A machine learning web application use to predict chances of heart disease, built with FLASK and deployed on Heroku.

Official implementation of our IEEE:SMC 2021 paper "IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification"

Udacity AI for Healthcare Nanodegree Project: Heart Rate Estimation Algorithm From PPG and Accelerometer data

4D reconstruction of developmental trajectories using spherical harmonics

First place solution for "medicine" topic in AI Challenge 2023

The objective of this project is to detect whether person has any chance of heart disease or not by giving number of features to person with having maximum accuracy of above 97%. By Using Machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset.

This project aims to develop a healthcare system that can predict multiple diseases, including liver disease, diabetes and heart disease using machine learning techniques. These are the most common types of Diseases that plaque the Indians today.