AI-ECG Amyloid (Image)

Yale School of Medicine (CarDS Lab)

12-lead ECG image

Filter catalog by Modality:
ECG

Cardiac amyloidosis

Filter catalog by Disease / Trait:
Structural Heart & Cardiomyopathy

Binary classification

Filter catalog by Task Type:
Classification

CNN (2D)

Filter catalog by Architecture:
Convolutional (CNN)

PyTorch

Filter catalog by Framework:
PyTorch

code View code

Model weights not public. Contact creators for more information.

CNN-based image classifier that screens 12-lead ECG images for a signature of transthyretin amyloid cardiomyopathy (ATTR-CM), producing a study-level probability score. Trained on a private Yale New Haven Health System cohort of nuclear-imaging-confirmed ATTR-CM cases and matched controls. Used alongside a companion echocardiography model to track pre-clinical ATTR-CM progression years before it would otherwise be confirmed by nuclear amyloid imaging. Developed by Yale's CarDS Lab and distributed as a packaged research-use executable rather than downloadable weights.

memory Specifications

description Publication

Tracking the Preclinical Progression of Transthyretin Amyloid Cardiomyopathy Using Artificial Intelligence-Enabled Electrocardiography and Echocardiography open_in_new

2024 · original paper

database Training & evaluation data

Yale New Haven Health System ATTR-CM ECG Cohort (AI-ECG Amyloid Image)

test

public 1,529 subjects · USA

139 ATTR-CM cases + 1,390 matched controls, held-out testing cohort

science Capabilities & performance