AI-assisted ECG interpretation significantly improved STEMI diagnostic accuracy and clinician confidence and the integration of AI-ECG decision-support tools into frontline and operational settings to enhance timely and accurate STEMI recognition is supported.
Adding AI-ECG signals to PREVENT-HF improves near-term heart-failure risk discrimination and reclassification, though without demonstrated benefit on clinical outcomes such as heart-failure hospitalization or mortality.
A. Bollmann, V. Pradler, D. Husser et al.· Frontiers in Cardiovascular...· 0 citations
Aims: Structural heart disease (SHD) often remains undetected until symptoms develop. Portable 1-lead ECG devices return an automated rhythm-based interpretation, but whether AI-ECG adds diagnostic value beyond this interpretation is unknown. We prospectively evaluated a noise-adapted 1-lead AI-ECG algorithm for detect...
A. Aminorroaya, S. Shankar, Mariam Khan et al.· medRxiv· 0 citations
For HF/LVSD, AI-ECG shows consistent and reproducible accuracy against echocardiography, and this estimate proved robust to the exclusion of studies at high risk of bias.
Joshuan J. Barboza, Óscar Andrés Ramírez-Terán, E. Tomás-Alvarado et al.· Diagnostics· 0 citations
BACKGROUND
Rapid and accurate electrocardiogram (ECG) interpretation is essential for timely identification of ST-elevation myocardial infarction (STEMI) and activation of reperfusion pathways in emergency care.
OBJECTIVES
To evaluate the diagnostic performance of multimodal LLMs in identifying prehospital ECGs warra...
Emile Legendre, U. Cvek, Stewart R. Greathouse et al.· Heart & lung : the journal o...· 0 citations
Artificial intelligence-enhanced electrocardiography demonstrated good diagnostic performance for detecting LVDD and may support future rule-out or risk-enrichment strategies in selected populations, however, current evidence remains insufficient to support routine clinical implementation.
Johann A. C. Edjimbi, Nisarg Shah, L. Donisi et al.· European Heart Journal - Dig...· 1 citation
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