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 ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...
Objective: To explore the risk factors of cognitive dysfunction in patients with leukoaraiosis (LA) and to construct a predictive model using machine learning. Methods: A total of 273 patients with LA ...
Abstract: Heart disease remains a leading cause of mortality worldwide. Accurate and timely diagnosis is crucial for effective treatment and prevention. This research proposes a novel approach using a ...
A newly enacted New York law requires retailers to say whether your data influences the price of basic goods like a dozen eggs or toilet paper, but not how. If you’re near Rochester, New York, the ...
A production-ready distributed rate limiter supporting five algorithms (Token Bucket, Sliding Window, Fixed Window, Leaky Bucket, and Composite) with Redis backing for high-performance API protection.
Abstract: Network coverage prediction is an important aspect of 4G network planning and optimization. In this study, we conducted a comprehensive analysis of the performance of various machine ...
Background: Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and ...
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