Objectives Since 1985, the international healthcare community has recommended the ideal rate of caesarean section (CS) to be 10%–15% at the national level. The literature has reported that overused CS ...
Abstract: Data mining, particularly multivariate time series data analysis, is crucial in extracting insights from complex systems and supporting informed decision-making across diverse domains.
Endovascular thrombectomy for large vessel occlusion stroke in patients with pre-existing disability
Background Approximately one in three patients with acute ischemic stroke (AIS) suffer from a premorbid disability prior to ...
Reporting quality in clinical research is critical for evidence-based medicine and reproducibility of clinical studies. Previous work has mostly focused on the reporting quality of clinical trials and ...
Previous studies on early pregnancy loss and breast cancer risk were often small and relied on self-reported data. This large Finnish registry study found no significant association between induced ...
Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Background Patients with heart failure (HF) and severe mitral regurgitation (MR) have poor outcomes. Early identification ...
Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...
Background Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in aortic stenosis (AS), ...
Background Despite several intensive interventions, HIV remains a major public health challenge affecting many individuals worldwide and highlighting ongoing gaps in HIV testing. Objectives To assess ...
Emotional support perceived through social media was statistically associated with lower anxiety among U.S. young adults, ...
Abstract: Learning-based motion planning methods have shown significant promise in enhancing the efficiency of traditional algorithms. However, they often face performance degradation in novel ...
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