AIMC Topic: Myocardial Infarction
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Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning.
Frontiers in immunology
Mar 21, 2025
BACKGROUND: Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.
Comparison of machine learning and nomogram to predict 30-day in-hospital mortality in patients with acute myocardial infarction combined with cardiogenic shock: a retrospective study based on the eICU-CRD and MIMIC-IV databases.
BMC cardiovascular disorders
Mar 19, 2025
BACKGROUND: To evaluate the predictive utility of machine learning and nomogram in predicting in-hospital mortality in patients with acute myocardial infarction complicated by cardiogenic shock (AMI-CS), and to visualize the model results in order to...
Predictive value of machine learning for in-hospital mortality risk in acute myocardial infarction: A systematic review and meta-analysis.
International journal of medical informatics
Mar 8, 2025
BACKGROUND: Machine learning (ML) models have been constructed to predict the risk of in-hospital mortality in patients with myocardial infarction (MI). Due to diverse ML models and modeling variables, along with the significant imbalance in data, th...
Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction.
Clinical medicine (London, England)
Feb 27, 2025
OBJECTIVE: We aim to develop and validate an interpretable machine-learning model that can provide critical information for the clinical treatment of critically ill patients with acute myocardial infarction (AMI).
The Evolving Paradigm of Myocardial Infarction in the Era of Artificial Intelligence.
British journal of hospital medicine (London, England : 2005)
Feb 23, 2025
The classification and treatment of myocardial infarction (MI) have evolved significantly over the past few decades, with the ST-segment elevation myocardial infarction (STEMI)/non-STEMI (NSTEMI) paradigm dominating clinical practice. While STEMI, id...
Development and validation of machine learning models based on stacked generalization to predict psychosocial maladjustment in patients with acute myocardial infarction.
BMC psychiatry
Feb 19, 2025
BACKGROUND: Psychosocial maladjustment threatens the recovery of patients with acute myocardial infarction (AMI), and early identification of patients with psychosocial maladjustment may facilitate provision of reference to targeted interventions. Th...
Prognostic Implications of Machine Learning Algorithm-Supported Diagnostic Classification of Myocardial Injury Using the Fourth Universal Definition of Myocardial Infarction.
Heart, lung & circulation
Feb 13, 2025
BACKGROUND: With widespread adoption of high-sensitivity troponin assays, more individuals with myocardial injury are now identified, with type 1 myocardial infarction (T1MI) being less common despite having the most well-established evidence base to...
Advancements and challenges in high-sensitivity cardiac troponin assays: diagnostic, pathophysiological, and clinical perspectives.
Clinical chemistry and laboratory medicine
Feb 7, 2025
Although significant progress has been made in recent years, some important questions remain regarding the analytical performance, pathophysiological interpretation and clinical use of cardiac troponin I (cTnI) and T (cTnT) measurements. Several rece...
Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction.
Drug safety
Feb 7, 2025
BACKGROUND: Safety signals for potential drug-induced adverse events (AEs) typically emerge from multiple data sources, primarily spontaneous reporting systems, despite known limitations. Increasingly, real-world data from sources such as electronic ...
Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.
Small (Weinheim an der Bergstrasse, Germany)
Feb 5, 2025
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations...
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