Machine Learning on ECG to predict heart-beat classification.

An explainable deep learning system for automated ECG arrhythmia detection using a hybrid 1D CNN–LSTM model with Grad-CAM–based clinical interpretability.

Arrhythmia detection using topological data analysis in combination with a convolutional neural network.

Production-ready ML system for automated ECG arrhythmia classification using MIT-BIH database

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).

An investigation into tabular classification with deep NNs for ETHZ Machine Learning for Healthcare on the MIT-BIH arrythmia dataset .

Deterministic ECG codec — Python + Rust, CI parity-gated. Bounded clinical-mode contract: PRD ≤ 2.32% on MIT-BIH (48/48, mean PRD 1.12%); PTB-XL boundary disclosed (max PRD 5.29%). Cardiologist-equivalence and regulatory closure out of scope.

Explainable ECG arrhythmia detection using 1D-CNN + SMOTE + SHAP on the MIT-BIH dataset | Deep Learning | XAI | Medical AI

MIT-BIH Arrhythmia Classification

Deep learning model for automated classification of cardiac arrhythmias using ECG signals from the MIT-BIH database. The project combines signal preprocessing via wavelet transform and a multi-layer CNN architecture, achieving over 98% test accuracy across 15 heartbeat classes. Designed for real-time and clinical applications.

Refactored PyTorch pipeline for 5-class ECG arrhythmia classification on MIT-BIH beat-level data. Silver Prize at KNOU Statistics & Data Analysis Competition '24

ECG heartbeat classification on the MIT‑BIH Kaggle dataset using SciPy signal features vs a 1‑D CNN, with careful imbalance handling and leakage checks. kaggle +1

ECG anomaly detection using LSTM Autoencoder on MIT-BIH Arrhythmia dataset — subject-aware DS1/DS2 split, PyTorch, with Isolation Forest baseline comparison

Reproducible pipeline for silent-failure auditing in ECG accept-sets (MIT-BIH) with Newton–Puiseux onset scoring