BACKGROUND: Acute kidney injury (AKI) and acute kidney disease (AKD) are prevalent among pediatric patients, both linked to increased mortality and extended hospital stays. Early detection of kidney injury is crucial for improving outcomes. This stud...
European journal of clinical investigation
Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
PURPOSE OF REVIEW: This review aims to explore the emerging potential of artificial intelligence (AI) in refining risk prediction, clinical diagnosis, and treatment stratification for cardiomyopathies, with a specific emphasis on arrhythmogenic cardi...
Heart failure is a complex and prevalent condition with significant implications for patient management and survival prediction. Traditional predictive models often fall short in accuracy due to their reliance on pre-specified predictors and assumpti...
Stroke is a leading cause of morbidity and mortality worldwide, and early detection of risk factors is critical for prevention and improved outcomes. Traditional stroke risk assessments, relying on sporadic clinical visits, fail to capture dynamic ch...
Journal of the American Heart Association
Dec 10, 2024
BACKGROUND: Machine learning (ML) techniques are widely employed across various domains to achieve accurate predictions. This study assessed the effectiveness of ML in predicting early mortality risk among patients with acute intracerebral hemorrhage...
Medical & biological engineering & computing
Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Journal of cardiothoracic and vascular anesthesia
Dec 9, 2024
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.
Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting 2 % of the European population. This prevalence increases with age, imposing signif...