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A newer version of the Gradio SDK is available: 6.14.0

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metadata 
title: SSL ECG Classification
emoji: 🌖
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 6.12.0
app_file: app.py
pinned: false
license: apache-2.0

ECG Classification with Self-Supervised Learning

DOI

Interactive Space for ECG cardiovascular disease classification using SimCLR pre-trained model fine-tuned on PTB-XL.

Quick Start

Upload an ECG file in any format (DICOM, MATLAB, HDF5, WFDB, CSV, and more) and get instant predictions across 5 diagnostic classes.

Model Performance

  • AUROC: 0.8717
  • Accuracy: 0.8234
  • Training Data: PTB-XL with 10% labeled samples (1,747 ECGs)

Supported File Formats

  • Clinical: DICOM (.dcm), SCP-ECG (.scp), HL7 aECG (.xml)
  • Research: WFDB (.hea/.dat), EDF (.edf)
  • Scientific: MATLAB (.mat), HDF5 (.h5), NumPy (.npy)
  • Generic: CSV/TXT/TSV, Binary (.raw, .bin)

Citation

If you use this model, please cite it using the DOI:

10.57967/hf/8469

Bibtex:

@model{ssrl_ecg_2024,
  title={SSL ECG Classification},
  doi={10.57967/hf/8469},
  url={https://huggingface.co/spaces/Tumo505/SSL-ECG-Classification},
  year={2024}
}

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