AIMC Topic: Acute Coronary Syndrome

Clear Filters Showing 51 to 60 of 72 articles

Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome.

Scientific reports Oct 6, 2016
Frequency domain measures of heart rate variability (HRV) are associated with adverse events after a myocardial infarction. However, patterns in the traditional frequency domain (measured in Hz, or cycles per second) may capture different cardiac phe...
Death Acute Coronary Syndrome Humans Machine Learning Predictive Value of Tests Electroencephalography Signal Processing, Computer-Assisted
View on PubMed DOI

Diagnosis of Acute Coronary Syndrome with a Support Vector Machine.

Journal of medical systems Jan 27, 2016
Acute coronary syndrome (ACS) is a serious condition arising from an imbalance of supply and demand to meet myocardium's metabolic needs. Patients typically present with retrosternal chest pain radiating to neck and left arm. Electrocardiography (ECG...
Male Middle Aged Decision Support Systems, Clinical Logistic Models Electrocardiography Support Vector Machine Age Factors Bayes Theorem Chest Pain Reproducibility of Results Risk Factors Aged Aged, 80 and over Sex Factors Adult Acute Coronary Syndrome Humans Troponin I Neural Networks, Computer Creatine Kinase, MB Form Female
View on PubMed DOI

Artificial neural network modeling enhances risk stratification and can reduce downstream testing for patients with suspected acute coronary syndromes, negative cardiac biomarkers, and normal ECGs.

The international journal of cardiovascular imaging Dec 1, 2015
Despite uncertain yield, guidelines endorse routine stress myocardial perfusion imaging (MPI) for patients with suspected acute coronary syndromes, unremarkable serial electrocardiograms, and negative troponin measurements. In these patients, outcome...
Coronary Stenosis Aged Male Middle Aged Risk Assessment Severity of Illness Index Humans Electrocardiography Neural Networks, Computer Coronary Artery Disease Prognosis Predictive Value of Tests Decision Support Techniques Acute Coronary Syndrome Retrospective Studies Coronary Angiography Biomarkers Tomography, Emission-Computed, Single-Photon Female Troponin Unnecessary Procedures Risk Factors Myocardial Perfusion Imaging
View on PubMed DOI

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome.

Journal of electrocardiology May 8, 2015
BACKGROUND AND PURPOSE: Culprit coronary artery assessment in the triage ECG of patients with suspected acute coronary syndrome (ACS) is relevant a priori knowledge preceding percutaneous coronary intervention (PCI). We compared a model-based automat...
Electrocardiography Coronary Artery Disease Expert Systems Reproducibility of Results Models, Cardiovascular Acute Coronary Syndrome Sensitivity and Specificity Humans Male Algorithms Middle Aged Computer Simulation Diagnosis, Computer-Assisted Female
View on PubMed DOI

MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.

Shock (Augusta, Ga.) Jul 1, 2025
Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and mortality. Machine learning (ML), combined with parameters such as shock indices, can potentially imp...
Humans Machine Learning Retrospective Studies Female Contrast Media Kidney Diseases Percutaneous Coronary Intervention Aged Shock Male Acute Coronary Syndrome Middle Aged Case-Control Studies
View on PubMed DOI

Derivation and validation of an artificial intelligence-based plaque burden safety cut-off for long-term acute coronary syndrome from coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging Jun 30, 2025
AIMS: Artificial intelligence (AI) has enabled accurate and fast plaque quantification from coronary computed tomography angiography (CCTA). However, AI detects any coronary plaque in up to 97% of patients. To avoid overdiagnosis, a plaque burden saf...
Computed Tomography Angiography Registries Reproducibility of Results Coronary Artery Disease Humans Aged Acute Coronary Syndrome Artificial Intelligence Middle Aged Sensitivity and Specificity Plaque, Atherosclerotic Female Risk Assessment Male Follow-Up Studies Predictive Value of Tests Coronary Angiography
View on PubMed DOI

Telecardiology unleashed: probing the depths of effectiveness in remote monitoring and telemedicine applications for acute cardiac conditions.

European heart journal. Acute cardiovascular care May 16, 2025
Telecardiology has emerged as a promising approach in acute cardiac care through advancements in digital health technologies. This review explores the current evidence of telemedicine applications in acute coronary syndrome, arrhythmias, and acute he...
Humans Electrocardiography Monitoring, Physiologic Acute Coronary Syndrome Acute Disease Cardiology Arrhythmias, Cardiac Telemedicine Heart Diseases
View on PubMed DOI

Machine Learning-Based Immuno-Inflammatory Index Integrating Clinical Characteristics for Predicting Coronary Artery Plaque Rupture.

Immunity, inflammation and disease Apr 1, 2025
BACKGROUND: Coronary artery plaque rupture (PR) is closely associated with immune-inflammatory responses. The systemic inflammatory index (SII) and the systemic inflammatory response index (SIRI) have shown potential in predicting the occurrence of P...
Aged Male Middle Aged ROC Curve Inflammation Humans Machine Learning Female Coronary Vessels Plaque, Atherosclerotic Tomography, Optical Coherence Percutaneous Coronary Intervention Coronary Artery Disease Acute Coronary Syndrome
View on PubMed DOI

Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome.

European heart journal Mar 7, 2025
BACKGROUND AND AIMS: The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to ...
Acute Coronary Syndrome Machine Learning Prospective Studies Prognosis Female Aged Male Middle Aged Risk Assessment Electrocardiography Humans
View on PubMed DOI

Stratification of Early Arrhythmic Risk in Patients Admitted for Acute Coronary Syndrome: The Role of the Machine Learning-Derived "PRAISE Score".

Clinical cardiology Dec 1, 2024
BACKGROUND: The PRAISE (PRedicting with Artificial Intelligence riSk aftEr acute coronary syndrome) score is a machine learning-based model for predicting 1-year adverse cardiovascular or bleeding events in patients with acute coronary syndrome (ACS)...
ROC Curve Predictive Value of Tests Atrial Fibrillation Acute Coronary Syndrome Male Middle Aged Risk Assessment Time Factors Humans Machine Learning Prospective Studies Prognosis Female Risk Factors Aged
View on PubMed DOI
Popular Topics
Recent Journals