The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabet...
International journal of medical informatics
Jul 3, 2024
BACKGROUND: Real-world data with decades-long medical records are increasingly available alongside the growing adoption of machine learning in healthcare research. We evaluated the performance of machine learning models in predicting the risk of Alzh...
IMPORTANCE: Sleep is critical to a person's physical and mental health and there is a need to create high performing machine learning models and critically understand how models rank covariates.
OBJECTIVE: Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynam...
BACKGROUND AND AIM: It is crucial to identify a diabetes diagnosis early. Create a predictive model utilizing machine learning (ML) to identify new cases of diabetes in primary health care (PHC).
PURPOSE: This study aims to develop and validate a prediction model for delirium in elderly ICU patients and help clinicians identify high-risk patients at the early stage.
Stroke stands as a major global health issue, causing high death and disability rates and significant social and economic burdens. The effectiveness of existing stroke risk assessment methods is questionable due to their use of inconsistent and varyi...
OBJECTIVE: The clinical manifestations of systemic sclerosis (SSc) are highly variable, resulting in varied outcomes and complications. Diverse fibrosis of the skin and internal organs, vasculopathy, and dysregulated immune system lead to poor and va...
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