A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...
A new Fracture Risk Assessment Tool that includes bone microarchitecture measures outperformed the current tool that uses ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
The final, formatted version of the article will be published soon. Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
Tua Tagovailoa should enjoy a fantasy football fiesta in Spain on Sunday. Sam Navarro / Imagn Images Though they’re ultimately two different lenses, sports betting can provide some smart intel for ...
Enhanced prediction capability: Machine learning-based system matches and in some cases outperforms traditional forecasting systems, with particular improvements in northern Europe where conventional ...
IN PATIENTS with cerebral infarction, machine learning models using neurophysiological and clinical data predicted ICU readmission. Logistic regression delivered the highest discrimination and offered ...
Abstract: Cognitive impairment, which commonly occurs after stroke, adversely impacts rehabilitation outcomes. The administration of traditional screening tools such as the Mini-Mental State ...
Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...
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