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Low Ejection Fraction

Artificial Intelligence–Enhanced Electrocardiography Identifies Patients With Normal Ejection Fraction at Risk of Worse Outcomes

Abstract Background An artificial intelligence (AI)-based electrocardiogram (ECG) model identifies patients with a higher likelihood of low ejection fraction (EF). Patients with an abnormal AI-ECG score but normal EF (false positives; FP) more often developed future low EF. Objective The purpose of… Read More

ScienceDirect

September 27, 2024

Low Ejection Fraction

Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial

Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. This open-label, pragmatic clinical trial randomized pregnant and postpartum women to usual care or artificial intelligence (AI)-guided screening to assess its impact on the diagnosis left ventricular systolic dysfunc… Read More

Nature Medicine

September 1, 2024

Cardiac Amyloidosis

Predictors of mortality by an artificial intelligence enhanced electrocardiogram model for cardiac amyloidosis

Aims We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA). Methods A total of 2533 patients with CA (1834 with light chain amyloidosis (AL), 530 with wild-type tr… Read More

Wiley Online Library

August 30, 2024

Low Ejection Fraction

Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure

We trained, validated, and tested an AI-enabled ECG in 98,736, 21,963, and 98,763 patients, respectively, who had an ECG and echocardiographic diastolic function assessment within 14 days with no exclusion criteria. It was also tested in 55,248 patients with indeterminate diastolic function by echoc… Read More

Nature Medicine

January 6, 2024

Hypertrophic Cardiomyopathy

Patient-Level Artificial Intelligence–Enhanced Electrocardiography in Hypertrophic Cardiomyopathy: Longitudinal Treatment and Clinical Biomarker Correlations

The purpose of this study was to determine if AI-enhanced ECG (AI-ECG) can track longitudinal therapeutic response and changes in cardiac structure, function, or hemodynamics in obstructive HCM during mavacamten treatment. We applied 2 independently developed AI-ECG algorithms (University of Califor… Read More

JACC

October 2, 2023

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