Overall, RS&LP demonstrated superior discriminative ability and generalizability, supporting its potential for clinical use, and future studies should validate these findings in larger multicenter cohorts to further improve ACS diagnosis and management directly in the ambulance.
Swift identification of cardiac events is crucial for enhancing patient outcomes. Electrocardiograms (ECGs) are noninvasive and can be quickly taken. Machine learning (ML) can then be used to assist in recognizing possible myocardial infarction. ECG recordings were extracted from a public database, and features related...
Chu-Tian Chen, V. Kouznetsova, I. Tsigelny· Medinformatics· 0 citations
CardioSmart Analyzer is an intelligent framework that automatically evaluates 12-lead electrocardiogram (ECG) measurements to identify a wide range of cardiovascular diseases (CVDs). The study introduces a machine-learning prediction pipeline for recognizing cardiac abnormalities from ECG-derived data. Twelve-lead ECG...
M. Alam, Razuan Karim, Md Ashikul Alam Khan· 2026 International Conferenc...· 0 citations
INTRODUCTION
Adequate prehospital triage of anterior-circulation LVO (aLVO) or ICH enables direct allocation to appropriate stroke centres. Traditional triage based on clinical scales or logistic regression may miss complex predictor interactions, whereas machine learning approaches may improve diagnostic accuracy. We...
B. L. Garcia, L. Dekker, René Bekker et al.· European Stroke Journal· 0 citations
Machine learning represents a promising tool for improving the accuracy of electrocardiogram-based prediction and early detection of myocardial infarction, however, broad clinical implementation requires methodological standardization, further prospective validation, and the development of interpretable and clinically...
Olga A. Stelmakh, A. Kravchenko· The Ukrainian Scientific Med...· 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
Remote monitoring of patients with CHF using artificial intelligence algorithms has proven its high clinical efficacy, significantly reducing the incidence of complications and readmissions for cardiovascular pathology.
P. Chomakhidze, D. Mesitskaya, Р. Р. Галимова et al.· Doctor Ru· 0 citations
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