Objectives To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in global and domain-specific cognitive function among US adults, using ...

Amyloid PET has become a pivotal imaging biomarker for Alzheimer disease (AD), enabling in vivo detection and quantification of β-amyloid deposition. However, variability in quantitative measurements ...

Introduction Implementing shared decision-making (SDM) in maternity care remains challenging in low-income and middle-income ...

AI-enhanced optical spectroscopy revolutionizes food quality monitoring with rapid, non-destructive analysis, ensuring safety and reducing waste in production.

In standard, multi-range FT-IR applications, the spectrometer must be opened to swap beamsplitters, requiring careful handling of expensive parts and exposing internal optics to the environment by ...

Researchers analyzed over 272,000 UK Biobank participants and used Mendelian randomization to investigate whether circulating ...

The explosive growth of electric vehicles, renewable energy integration, and large-scale energy storage systems has placed ...

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.

Introduction Previous reviews have investigated the relationship between empathy and burnout. However, these are now out of date, did not capture the effect of the pandemic, did not include healthcare ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Abstract: Linear discriminant analysis (LDA) is a widely used technique for data classification. The method offers adequate performance in many classification problems, but it becomes inefficient when ...