Abstract: To address sparse channel measurement data and inadequate predictive capabilities in conventional channel models, predictive channel modeling employs joint generative and predictive ...

Healthcare leaders in North Texas are identifying and addressing maternal health risks early, aiming to improve outcomes in a region with some of the worst maternal health statistics in the country.

Predictive modeling in archaeological site location combines statistical and computational techniques with spatial analysis to estimate the likelihood of undiscovered cultural heritage across diverse ...

Predictive modeling of hydrological time series aims to forecast variables such as streamflow, runoff and reservoir inflows by analysing past measurements and environmental drivers. These data are ...

The global community has faced substantial threats from infectious diseases in recent decades. As a crucial element of epidemic surveillance systems, infectious disease prediction technology plays an ...

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The techniques that have served marketers for over fifty years are evolving rapidly, driven by artificial intelligence, increasing market volatility and a fundamental shift in what we expect ...

Abstract: This paper presents predictive modeling frame for the early-stage diagnosis of Parkinson's Diseases by integrating both ensemble-based and statistical machine learning algorithms. This works ...

Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after spontaneous intracerebral hemorrhage (ICH). An incomplete understanding of its biophysiology has limited ...

Researchers have developed and validated predictive models to estimate the core pain-processing mechanisms using a limited set of easily accessible, routinely obtainable clinical measures. Researchers ...