https://github.com/ai4healthuol/sssd-ecg

Repository for the paper: 'Diffusion-based Conditional ECG Generation with Structured State Space Models'

https://github.com/ai4healthuol/sssd-ecg

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org, sciencedirect.com, zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.8%) to scientific vocabulary

Keywords

conditional-generation diffusion-models ecg-signals healthcare
Last synced: 6 months ago · JSON representation

Repository

Repository for the paper: 'Diffusion-based Conditional ECG Generation with Structured State Space Models'

Basic Info
  • Host: GitHub
  • Owner: AI4HealthUOL
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 8.69 MB
Statistics
  • Stars: 55
  • Watchers: 2
  • Forks: 9
  • Open Issues: 0
  • Releases: 2
Topics
conditional-generation diffusion-models ecg-signals healthcare
Created about 3 years ago · Last pushed 11 months ago
Metadata Files
Readme

README.md

Diffusion-based Conditional ECG Generation with Structured State Space Models

This is the official repository for the paper Diffusion-based Conditional ECG Generation with Structured State Space Models accepted by Computers in Biology and Medicine. We propose diverse algorithms (primarly SSSD-ECG) for the generation of 12-lead ECG signals conditioned on disease labels.

arXiv

alt text

Please cite our publication if you found our research to be helpful.

```bibtex @article{ALCARAZ2023107115, title = {Diffusion-based conditional ECG generation with structured state space models}, journal = {Computers in Biology and Medicine}, volume = {163}, pages = {107115}, year = {2023}, issn = {0010-4825}, doi = {https://doi.org/10.1016/j.compbiomed.2023.107115}, url = {https://www.sciencedirect.com/science/article/pii/S0010482523005802}, author = {Juan Miguel Lopez Alcaraz and Nils Strodthoff}, keywords = {Cardiology, Electrocardiography, Signal processing, Synthetic data, Diffusion models, Time series}, }

```

Owner

  • Name: AI4HealthUOL
  • Login: AI4HealthUOL
  • Kind: organization
  • Location: Germany

Public repositories of the AI4Health Division at Oldenburg University

GitHub Events

Total
  • Issues event: 12
  • Watch event: 24
  • Issue comment event: 12
  • Push event: 3
  • Fork event: 7
Last Year
  • Issues event: 12
  • Watch event: 24
  • Issue comment event: 12
  • Push event: 3
  • Fork event: 7

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 5
  • Total pull requests: 0
  • Average time to close issues: 18 days
  • Average time to close pull requests: N/A
  • Total issue authors: 4
  • Total pull request authors: 0
  • Average comments per issue: 1.2
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 5
  • Pull requests: 0
  • Average time to close issues: 18 days
  • Average time to close pull requests: N/A
  • Issue authors: 4
  • Pull request authors: 0
  • Average comments per issue: 1.2
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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  • Ssw2001 (1)
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