Automatic 12-lead ECG diagnosis DNN

Universidade Federal de Minas Gerais (UFMG)

12-lead ECG

Filter catalog by Modality:
ECG

General Purpose / Multi-task

Filter catalog by Disease / Trait:
General / Foundation

Multi-label classification

Filter catalog by Task Type:
Classification

CNN (1D)

Filter catalog by Architecture:
Convolutional (CNN)

TensorFlow

Filter catalog by Framework:
TensorFlow / Keras

CC BY 4.0

Filter catalog by License:
Open — Attribution

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1D residual neural network that screens 10-second, 12-lead ECG tracings for six common abnormalities: first- and second-degree AV block patterns, right and left bundle branch block, sinus bradycardia, atrial fibrillation, and sinus tachycardia. Reported F1 scores above 80% and specificity over 99% when benchmarked against cardiology residents. Developed at Universidade Federal de Minas Gerais and trained on the large Brazilian CODE-15% ECG dataset.

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

Automatic diagnosis of the 12-lead ECG using a deep neural network open_in_new

2020 · original paper

DOI: 10.1038/s41467-020-15432-4

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