Related Experiment Video
Updated: Mar 20, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
Published on: April 11, 2025
Artificial intelligence-enhanced electrocardiography for identifying subclinical left ventricular dysfunction in
1TC Saglik Bakanligi Bolu Izzet Baysal Devlet Hastanesi, Bolu, Türkiye.
Background:
Subclinical left ventricular (LV) impairment-characterized by reduced global longitudinal strain (GLS) despite normal left ventricular ejection fraction (LVEF)-is frequently encountered in hypertensive patients. While speckle-tracking echocardiography is the standard method for detecting early myocardial dysfunction, it is not universally available. Artificial intelligence-enhanced electrocardiography (AI-ECG) has emerged as a promising tool capable of uncovering subtle electrical patterns linked to early myocardial impairment. This study investigates the diagnostic capability of AI-ECG for detecting GLS-defined subclinical LV dysfunction.
Methods:
In this retrospective analysis, 348 hypertensive adults who underwent both ECG and echocardiography within the same clinical visit (2022-2024) were evaluated. Subclinical LV dysfunction was defined as LVEF ≥50% and GLS > -18%.A convolutional neural network-based AI algorithm generated an AI-ECG probability score (range 0-1) representing the likelihood of LV dysfunction. Statistical analyses included correlation testing, regression modeling, and ROC curve evaluation.
Results:
Subclinical LV dysfunction was identified in 134 participants (38.5%). The AI-ECG probability score differed markedly between the abnormal GLS group and the normal GLS group (0.61 ± 0.20 vs. 0.29 ± 0.18; p < 0.001). GLS values demonstrated a strong negative association with AI-ECG scores (r = -0.63). ROC analysis showed robust diagnostic ability with an AUC of 0.86 (95% CI: 0.82-0.89). In multivariable logistic regression adjusting for LV mass index, E/e', age, and hypertension duration, the AI-ECG probability score remained independently associated with subclinical LV dysfunction (adjusted OR 1.12 per 0.1 increase, 95% CI 1.07-1.18; p < 0.001).
Conclusion:
AI-ECG accurately detects GLS-defined subclinical LV dysfunction in hypertensive adults and may serve as an accessible tool for early risk stratification in routine clinical settings.
More Related Videos
05:03Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
Published on: December 11, 2019
18:11A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
Published on: December 28, 2012
Related Concept Videos
Electrocardiogram
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
Hypertension III: Clinical Manifestations and Diagnostic Studies
Dysrhythmias V: Evaluating Dysrhythmias
Acute Coronary Syndrome III: Diagnostic Studies
Electrocardiogram Fundamentals
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
Imaging Studies for Cardiovascular System I:Echocardiography
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...