Background: Diet and nutrients are emerging key players in neurological disorders. Attention-Deficit/Hyperactivity Disorder (ADHD) is a major neurodevelopmental ...
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Abstract: While machine learning methods have significantly improved model performance over traditional methods, their black-box structure makes it difficult for researchers to interpret results. For ...
Introduction: Various mathematical equations have been proposed to correct QT interval for heart rate (QTc). However, with most formulas, QTc remains dependent on heart rate (HR) especially at low and ...
Introduction: Machine performance has surpassed human capabilities in various tasks, yet the opacity of complex models limits their adoption in critical fields such as healthcare. Explainable AI (XAI) ...
Abstract: Spectrum sensing in cognitive radio presents a challenge in overcoming the spectrum scarcity caused by the rapid growth of wireless devices. Deep learning (DL) and machine learning (ML) are ...
ABSTRACT: Soil pH is a critical indicator of soil health and fertility, influencing nutrient availability and crop productivity. Leveraging real-time sensor technology allows for high-resolution data ...
ABSTRACT: As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as ...
Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...
MorphoGAM is an R package that provides statistical tools for modeling spatial gene expression data along one-dimensional paths. The package implements a two-step approach: first, it estimates a ...
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