ECG-age ResNet (ecg-age-prediction)

Uppsala University / UFMG (Lima et al.)

12-lead ECG

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ECG

Cardiac aging / biological age

Filter catalog by Disease / Trait:
Prognosis & Aging

Regression

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Regression

CNN (1D)

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Convolutional (CNN)

PyTorch

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PyTorch

CC BY 4.0

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Open — Attribution

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1D residual neural network that predicts a patient's age directly from a 12-lead ECG; the gap between this predicted 'ECG age' and true chronological age is used as a biomarker of cardiovascular risk and mortality. Trained on the CODE-15% Brazilian ECG dataset, with the original R² of 0.71 later reproduced (R² = 0.70) in an independent German validation cohort. Developed by researchers at Uppsala University and UFMG.

memory Specifications

gavel License

CC BY 4.0

check_small Open source check_small Commercial use OK check_small Modifications allowed Attribution required No share-alike requirement

License for model weights only. Associated code may be licensed seperately, check code source for specific terms.

description Publication

Deep neural network-estimated electrocardiographic age as a mortality predictor open_in_new

2021 · original paper

DOI: 10.1038/s41467-021-25351-7

database Training & evaluation data

CODE-15% open_in_new

train

Brazil

Publicly available 15% subset of the CODE (Clinical Outcomes in Digital Electrocardiology) dataset from the Telehealth Network of Minas Gerais; full CODE dataset (>2 million exams) is request-only.

science Capabilities & performance

ECG-predicted age

Regression Cardiac aging / biological age

0.71 R-squared CODE test set · internal

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