ArticleScientific reports2024
Point-of-care AI-enhanced novice echocardiography for screening heart failure (PANES-HF).
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Decentralized community-based hub-intermediary-spoke model for rapid cardiac ultrasound triage for early heart failure detection: findings from the Heart2Miss initiative.European heart journal. Digital health · 2026Article
- Task-shifting to nonexperts using artificial intelligence-guided point-of-care ultrasound: a cohort study of patient selection, image quality, and learning curves.European heart journal. Imaging methods and practice · 2026Article
- The Evolving Utility of Artificial Intelligence-Based Tools for the Detection of Heart Failure and Cardiomyopathies: From Potential to Implementation.Current heart failure reports · 2026Review
- Emerging Artificial Intelligence Tools for the Screening of Structural and Valvular Heart Disease.Current heart failure reports · 2026Review
- AI task-shifting for echocardiographic LVEF assessment in Singapore: an economic evaluation.ESC heart failure · 2026Article
- Artificial Intelligence and Digital Technology in Cardiovascular Imaging: A Narrative Review.Biotech (Basel (Switzerland)) · 2026Review
- Artificial intelligence-enhanced echocardiography in cardiovascular disease management.Nature reviews. Cardiology · 2026Review
- The effect of AI-assisted bedside echocardiography on inpatient care: a prospective trial.European heart journal. Digital health · 2026Article
- Artificial Intelligence in Sports Cardiology: Advancing Cardiovascular Screening and Diagnosis.Cureus · 2026Review
- Finding and Managing Heart Failure Earlier: Why Enhancing Primary Care Teams to Apply More Definitive Surveillance is the Solution.Cardiac failure review · 2026Review
- Use of artificial intelligence for detecting left ventricular dysfunction and predicting incident heart failure risk.ESC heart failure · 2025Review
- Effectiveness of traditional, artificial intelligence-assisted, and virtual reality training modalities for focused cardiac ultrasound skill acquisition: a randomised controlled study.The ultrasound journal · 2025Article
- AI-Assisted Handheld Echocardiography by Nonexpert Operators: A Narrative Review of Prospective Studies.Cureus · 2025Review
- AI assisted focused cardiac ultrasound in preventive cardiology - a perspective.NPJ cardiovascular health · 2025Review
- Reliability of spectral Doppler in handheld ultrasonographic device.The international journal of cardiovascular imaging · 2025Article
- Leveraging Comprehensive Echo Data to Power Artificial Intelligence Models for Handheld Cardiac Ultrasound.Mayo Clinic proceedings. Digital health · 2025Article
- Harnessing Artificial Intelligence for Innovation in Interventional Cardiovascular Care.Journal of the Society for Cardiovascular Angiography & Interventions · 2025Review
- The role of artificial intelligence in standardizing global longitudinal strain measurements in echocardiography.European heart journal. Imaging methods and practice · 2024Article
- A deep learning model for classifying left ventricular enlargement for both transthoracic echocardiograms and handheld cardiac ultrasound.European heart journal. Imaging methods and practice · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing prevalence of heart failure (HF) in ageing populations drives demand for echocardiography (echo). There is a worldwide shortage of trained sonographers and long waiting times for expert echo. We hypothesised that artificial intelligence (AI)-enhanced point-of-care echo can enable HF screening by novices. The primary endpoint was the accuracy of AI-enhanced novice pathway in detecting reduced LV ejection fraction (LVEF) < 50%. Symptomatic patients with suspected HF (N = 100, mean age 61 ± 15 years, 56% men) were prospectively recruited. Novices with no prior echo experience underwent 2-weeks' training to acquire echo images with AI guidance using the EchoNous Kosmos handheld echo, with AI-automated reporting by Us2.ai (AI-enhanced novice pathway). All patients also had standard echo by trained sonographers interpreted by cardiologists (reference standard). LVEF < 50% by reference standard was present in 27 patients. AI-enhanced novice pathway yielded interpretable results in 96 patients and took a mean of 12 min 51 s per study. The area under the curve (AUC) of the AI novice pathway was 0.880 (95% CI 0.802, 0.958). The sensitivity, specificity, positive predictive and negative predictive values of the AI-enhanced novice pathway in detecting LVEF < 50% were 84.6%, 91.4%, 78.5% and 94.1% respectively. The median absolute deviation of the AI-novice pathway LVEF from the reference standard LVEF was 6.03%. AI-enhanced novice pathway holds potential to task shift echo beyond tertiary centres and improve the HF diagnostic workflow.
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