---
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}
}
```