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ECGTransForm

imported

software/ecgtransform

[Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer

Machine-generated from the listed sources and not yet reviewed by a human.

ECGTransForm project image
GitHub preview card for emadeldeen24/ECGTransForm. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
adaptive · arrhythmia-classification · cnn · ecg · ecg-classification · self-attention · time-series · transformer
Regulatory
unknown
built by · 1

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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  • EDIcnn · ecg · ecg-classification

    A Method to Improve Any ECG Denoising Technique In limb leads

  • ECG-DigitizeNet: A complete end-to-end system that converts raw 12-lead ECG images into digitized time-series signals, classifies cardiac conditions using a Hybrid CNN–Transformer (ViT-like) deep…

  • TC-CoNetcnn · transformer

    [Computers in Biology and Medicine - 2023] This is an official PyTorch implementation for Collaborative networks of Transformers and Convolutional neural networks are powerful and versatile learners…

  • ADASTself-attention

    [IEEE TETCI] "ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training"

sources
  1. api.github.com/repos/emadeldeen24/ECGTransForm
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2025-04-30, 74 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/34.json→ .entries["ecgtransform"]

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