ArticleEuropean heart journal. Digital health2026
Evaluation of artificial intelligence-based electrocardiogram analysis tools in patients with hypertrophic cardiomyopathy.
Article in European heart journal. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Point-of-care echocardiography screening for hypertrophic cardiomyopathy using automated deep-learning analysis.European heart journal. Digital health · 2026Article
- Diagnostic Accuracy of Artificial Intelligence-Based Electrocardiography for the Detection of Heart Diseases: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Disease-focused evaluation of AI-ECG tools: clarifying study design, findings, and the principles of open science.European heart journal. Digital health · 2026Article
- Review
- Open science requires trust and rigour: a framework for responsible evaluation of shared AI-ECG tools.European heart journal. Digital health · 2026Article
Corrections and comments
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Authors and funding
16 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Aims: Artificial intelligence (AI)-based electrocardiogram (ECG) analysis tools have shown promise in detecting various cardiac conditions. However, their performance in specific patient populations, such as those with hypertrophic cardiomyopathy (HCM), remains incompletely characterized. To evaluate the performance of three AI-based ECG analysis tools in patients with confirmed HCM: (1) a tool calculating HCM probability, (2) a tool calculating structural heart disease (SHD) probability, and (3) a tool providing ECG-based diagnoses across multiple categories. Methods and results: We analysed digitized 12-lead ECGs from patients with confirmed HCM ( Conclusion: AI-based ECG analysis tools demonstrated modest performance in our HCM cohort. These findings highlight the challenges of applying AI tools developed in general populations to specific disease cohorts and underscore the need for disease-specific validation before clinical implementation.
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