CLEF-Medium

Nokia Bell Labs

Single-lead ECG

Filter catalog by Modality:
ECG

General Purpose / Multi-task

Filter catalog by Disease / Trait:
General / Foundation

Embedding

Filter catalog by Task Type:
Representation Learning

Transformer

Filter catalog by Architecture:
Transformer

PyTorch

Filter catalog by Framework:
PyTorch

BSD 3-Clause

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Permissive

file_copy

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Single-lead ECG foundation model pretrained with clinically-guided contrastive learning: rather than relying on hand-labeled tasks, it uses routinely collected clinical metadata and risk scores from 161,000 MIMIC-IV-ECG patients as the training signal. Released in three sizes - Small (~448K parameters), Medium (30.7M), and Large (~296M) - and benchmarked against other ECG foundation models like ECGFounder across 18 tasks and 7 held-out datasets. Developed by Nokia Bell Labs.

memory Specifications

gavel License

BSD 3-Clause

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

CLEF: Clinically-Guided Contrastive Learning for Electrocardiogram Foundation Models open_in_new

2025 · original paper

database Training & evaluation data

MIMIC-IV-ECG open_in_new

train

public 161,352 subjects · USA

800,035 12-lead ECG-report pairs from 161,352 subjects at Beth Israel Deaconess Medical Center.

science Capabilities & performance