| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - ecg |
| - biological-age |
| - cardiology |
| - pytorch |
| - uk-biobank |
| --- |
| |
| # Beat-age |
|
|
| This is the official checkpoint release for the paper: |
|
|
| **Beat-Level Electrocardiographic Biological Age and Its Variability as Digital Biomarkers for Cardiovascular Risk Stratification** |
|
|
| Official GitHub repository: https://github.com/chiangfish/beat-age |
|
|
| ## Files |
|
|
| - `v1_best.pth`: Beat-age beat-level Net1D checkpoint trained on the UK Biobank Development Cohort. |
| - `ckpt_manifest.json`: checkpoint metadata, including file size, SHA-256 checksum, architecture, and intended use. |
|
|
| ## Model |
|
|
| Beat-age is a beat-level ECG biological age model. It predicts biological age from individual segmented 12-lead cardiac cycles and aggregates beat-level predictions at the ECG-recording level. |
|
|
| - Architecture: one-dimensional residual CNN (`Net1D`) |
| - Input: segmented 12-lead ECG beats |
| - Output: predicted biological age in years |
| - Age gap: predicted age minus chronological age |
|
|
| ## Usage |
|
|
| Download the checkpoint and place it under `ckpts/` in the GitHub repository: |
|
|
| ```bash |
| mkdir -p ckpts |
| hf download chiangfish/beat-age v1_best.pth --local-dir ckpts |
| ``` |
|
|
| Then run the inference scripts from the GitHub repository following its README. |
|
|
| ## Data |
|
|
| The model was developed using controlled-access UK Biobank ECG data. Downstream external validation used MIMIC-IV-ECG. These datasets are not redistributed in this model repository. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{beatage2026, |
| title = {Beat-Level Electrocardiographic Biological Age and Its Variability as Digital Biomarkers for Cardiovascular Risk Stratification}, |
| author = {Zirui Jiang, Guangkun Nie, Qinghao Zhao, and Shenda Hong}, |
| year = {2026} |
| } |
| ``` |
|
|
