Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Abstract: Robust model predictive control (MPC) algorithms are essential for addressing unavoidable errors due to the uncertainty in predicting real-world systems. However, the formulation of such ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
Opinion
Morning Overview on MSNOpinion
Firms hire AI specialists over data engineers, and it’s backfiring
Corporate leaders are racing to hire artificial intelligence talent, convinced that a few high-profile specialists can transform their businesses overnight. Instead, many are discovering that without ...
In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Abstract: Implementing model predictive control (MPC) in practice faces many subtle but prevalent problems, including modeling errors, solver errors, and actuator faults. In essence, the real control ...
In this example, we demonstrate how to model power electronics devices that perform current control using MathWorks products, focusing on: The modeling style introduced in this example is not a ...
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