AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...
WebMD

Electrocardiograms (ECG or EKG)

An electrocardiogram, also called an ECG or EKG, is a simple and painless test that measures the electrical impulses of your heart to check for signs of heart disease. It's done through small ...
Scientific Research Publishing

Natekin, A. and Knoll, A. (2013) Gradient Boosting Machines, a Tutorial. Frontiers in Neurorobotics, 7, Article No. 21.

ABSTRACT: Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and ...
GitHub

jellylemonshake/ECG-Disease-Detection-with-Deep-Learning

End-to-end machine learning pipeline for automatic diagnosis of cardiac diseases and arrhythmias from 12-lead ECGs using the PTB-XL dataset (PhysioNet). The project trains deep neural networks on ...
IEEE

An Optimized Machine Learning Model for R and T Peak Detection in ECG Signal

Abstract: Detection of R and T peaks in electrocardiogram (ECG) signals is essential for monitoring and diagnosing heart-related diseases. In generic cases, these peaks suffer through different types ...
GitHub

A collection of machine learning examples and tutorials.

Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were done in Google Colab. Therefore, you should check the ...
IEEE

Classification of ECG patterns for diagnostic purposes by means of Neural Networks and Support Vector Machines

Abstract: This paper presents an application of Neural Networks (NNs) and Support Vector Machines (SVMs) for the detection and classification of heartbeats in electrocardiogram (ECG) signals. The ...