An advanced ECG anomaly detection system using deep learning. This repository contains a CNN autoencoder trained on the PTBDB dataset to identify abnormal heart rhythms. It employs various loss functions for model optimization and provides comprehensive visualizations of the results.

Проект машинного обучения для анализа электрокардиограмм (ЭКГ) с использованием сиамских нейронных сетей для обучения с малым количеством примеров (few-shot learning). Этот проект реализует подход глубокого обучения для анализа сигналов ЭКГ и обнаружения сердечных аномалий.

Biomedical Signal & Image Processing Lab Projects.

Spectral analysis of ECG signals based on Fast Fourier Transform and Power Spectral Density

Newton–Puiseux for CVNNs: complete toolkit for uncertainty mining, confidence calibration and local symbolic-numeric analysis on ECG (MIT-BIH) and wireless IQ data (RadioML 2016.10A).

Heartbeat detection from ECG signals using filtering and R-peak analysis in MATLAB.

EKG Vision - A modern Flutter application for medical professionals to analyze ECG/EKG scans with AI-powered detection. Features secure doctor authentication, patient management, real-time ECG analysis, and a responsive UI with light/dark themes. Built with Flutter for cross-platform compatibility and Python Flask backend for robust data processing