Heart failure & cardiomyopathies
Artificial Intelligence–Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study
Authors' conclusion
In this first-in-kind independent validation and head-to-head comparison study, AI-ECG for LVSD detection demonstrated strong performance despite training on disparate populations. However, the limited-availability of models hinders independent validation.
Study context
- Population
- Patients undergoing routine clinical cardiac magnetic resonance imaging with paired ECGsall patients in external validation cohort, mean age 59 ± 15 years, 450 [35%] female
- Participants
- 1,203 patients
- Comparison
- Published AI-ECG models for left ventricular systolic dysfunction (LVSD) detection compared head-to-head against cardiologist-adjudicated cardiac magnetic resonance imaging reports
- All patientsn = 1,203
Methodological detailsindependent validation and head-to-head comparison study, risk of bias assessment, well-phenotyped registry of patients undergoing routine clinical cardiac magnetic resonance imaging with cardiologist-adjudicated reports and paired ECGs, all consecutive patients
- Independent validation and head-to-head comparison study
- Risk of bias assessment
- Well-phenotyped registry of patients undergoing routine clinical cardiac magnetic resonance imaging with cardiologist-adjudicated reports and paired ECGs
- All consecutive patients
Pooled result
As reported in the abstract
Systematic review: published AI-ECG models predicting LVSD
Studies identified
35
Models described
51
Groups sharing models for independent testing (from Korea, the United States, Taiwan, and the Netherlands)
Four
Further pooled results
| Outcome | All patients | Lower-complexity subgroup |
|---|---|---|
| AUROC for LVSD detection | AUROC range 0.83 to 0.93 | AUROC range 0.87 to 0.96 |
Performance across subgroups
- Performance remained consistent across subgroups, with slight decreases in ECGs showing wide QRS complexes or atrial fibrillation
Original publication
Artificial Intelligence–Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study. JACC Adv. Published 20 January 2026. doi:10.
Summarised from the published abstract; every number is checked against it