AIMC Topic: Myocardial Infarction
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Identification and validation of ANXA3 and SOCS3 as biomarkers for acute myocardial infarction related to sphingolipid metabolism.
Hereditas
Aug 4, 2025
BACKGROUND: Sphingolipid metabolism (SM) is linked to acute myocardial infarction (AMI), but its role remains unclear. This study explored SM-related genes (SMRGs) in AMI to support clinical diagnosis.
Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation.
Nature communications
Jul 31, 2025
Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying biological mechanisms remain unclear. We evaluate a panel of 12 circulating biomarkers representing diverse pathophysiological pathways in 3817 AF patien...
Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data.
Scientific reports
Jul 31, 2025
Myocardial infarction (MI) remains one of the greatest contributors to mortality, and patients admitted to the intensive care unit (ICU) with myocardial infarction are at higher risk of death. In this study, we use two retrospective cohorts extracted...
Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.
Journal of translational medicine
Jul 23, 2025
BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently overlooked in clinical practice. It poses significant challenges in treatment, leading to poor long-term prognosis and substantial economic burden on pat...
Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach.
Scientific reports
Jul 20, 2025
Acute myocardial infarction (AMI) is a serious heart disease with high fatality rates. The progress of AMI involves immune cell infiltration. However, suitable clinical diagnostic biomarkers and the roles of immune cells in AMI remain unknown. Three ...
Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis.
Journal of medical Internet research
Jul 18, 2025
BACKGROUND: Machine learning (ML) models may offer greater clinical utility than conventional risk scores, such as the Thrombolysis in Myocardial Infarction (TIMI) and Global Registry of Acute Coronary Events (GRACE) risk scores. However, there is a ...
Comparison of conventional and radiomics-based analysis of myocardial infarction using multimodal non-linear optical microscopy.
Scientific reports
Jul 18, 2025
Myocardial infarction, a leading cause of mortality worldwide, leaves survivors at significant risk of recurrence caused by scar-related re-entrant ventricular tachyarrhythmias. Effective treatment with ablation therapy requires a precise guidance sy...
Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.
Scientific reports
Jul 8, 2025
Robust differentiation between infarcted and normal myocardial tissue is essential for improving diagnostic accuracy and personalizing treatment in myocardial infarction (MI). This study proposes a hybrid framework combining radiomic texture analysis...
Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above.
BMC geriatrics
Jul 2, 2025
BACKGROUND: Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular condition mainly affecting individuals aged 75 and above, who are at higher risk of mortality due to age-related vulnerabilities and other health issues...
Identification of key genes associated with cellular aging and mitochondria in acute myocardial infarction.
Scientific reports
Jul 1, 2025
Acute myocardial infarction (AMI) poses a significant global mortality burden. Utilizing bio informatics, this study explored cellular aging-related genes (CARGs) and mitochondrial-related genes (MRGs). in AMI Public AMI datasets were analyzed using ...
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