AIMC Topic: ST Elevation Myocardial Infarction
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Development of Clinically Validated Artificial Intelligence Model for Detecting ST-segment Elevation Myocardial Infarction.
Annals of emergency medicine
Jul 26, 2024
STUDY OBJECTIVE: Although the importance of primary percutaneous coronary intervention has been emphasized for ST-segment elevation myocardial infarction (STEMI), the appropriateness of the cardiac catheterization laboratory activation remains subopt...
AI-enabled ECG index for predicting left ventricular dysfunction in patients with ST-segment elevation myocardial infarction.
Scientific reports
Jul 17, 2024
Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are associated with prognosis. This study investigated the feasibility of predicting left ventricula...
Uncovering STEMI patient phenotypes using unsupervised machine learning.
International journal of cardiology
Jul 9, 2024
Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.
International journal of cardiology
Jun 15, 2024
BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis.
Ensemble machine learning for predicting in-hospital mortality in Asian women with ST-elevation myocardial infarction (STEMI).
Scientific reports
May 29, 2024
The accurate prediction of in-hospital mortality in Asian women after ST-Elevation Myocardial Infarction (STEMI) remains a crucial issue in medical research. Existing models frequently neglect this demographic's particular attributes, resulting in po...
1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.
Medicina (Kaunas, Lithuania)
Mar 29, 2024
: Patients presenting with ST Elevation Myocardial Infarction (STEMI) due to occlusive coronary arteries remain at a higher risk of excess morbidity and mortality despite being treated with primary percutaneous coronary intervention (PPCI). Identifyi...
Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning.
IEEE journal of translational engineering in health and medicine
Dec 8, 2022
OBJECTIVE: Early revascularization of the occluded coronary artery in patients with ST elevation myocardial infarction (STEMI) has been demonstrated to decrease mortality and morbidity. Currently, physicians rely on features of electrocardiograms (EC...
Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients.
Scientific reports
Nov 15, 2022
Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a l...
Kenichi Harumi Plenary Address at Annual Meeting of the International Society of Computers in Electrocardiology: "What Should ECG Deep Learning Focus on? The diagnosis of acute coronary occlusion!".
Journal of electrocardiology
Nov 5, 2022
According to the STEMI paradigm, only patients whose ECGs meet STEMI criteria require immediate reperfusion. This leads to reperfusion delays and significantly increases the mortality for the quarter of "non-STEMI" patients with totally occluded arte...
Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction.
Scientific reports
Jul 18, 2022
Feasibility of automated volume-derived cardiac functional evaluation has successfully been demonstrated using cardiovascular magnetic resonance (CMR) imaging. Notwithstanding, strain assessment has proven incremental value for cardiovascular risk st...
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