Cardiovascular and neurological diseases are a major cause of mortality and morbidity
worldwide. Such diseases require careful monitoring to effectively manage their …

Background: Thrombolytic therapy is essential for acute ischemic stroke (AIS) management
but poses a risk of hemorrhagic transformation (HT), necessitating accurate prediction to …

Objective To develop logistic regression nomogram and machine learning (ML)-based
models to predict 3-month unfavorable functional outcome for acute ischemic stroke (AIS) …

Aim The objective of this study is to develop accurate machine learning (ML) models for
predicting the neurological status at hospital discharge of critically ill patients with …

This study conducted a comprehensive patent and bibliometric analysis to elucidate the
evolving scientific landscape surrounding the development and application of pulse …

Background Research into the acute kidney disease (AKD) after acute ischemic stroke (AIS)
is rare, and how clinical features influence its prognosis remain unknown. We aim to employ …

Background The inflammatory response holds paramount significance in the context of
intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates …

We investigated the relationship among red cell distribution width (RDW), to total serum
calcium (TSC) ratio (RCR), and in-hospital mortality in patients with acute ischemic stroke …

Objective This study aims to develop risk prediction models for neck and shoulder
musculoskeletal disorders among healthcare professionals. Methods A stratified sampling …

The integration of bioinformatics analysis into intracerebral hemorrhage (ICH) research
represents a paradigm shift in our approach to understanding, diagnosing, and treating this …