IEEE

Practical Nonlinear Model Predictive Control With Kolmogorov–Arnold Network Models

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Google Antigravity & Stitch Build a Real AI Applications : No Code Workflows

Agentic Postgres from Tiger Data offers persistent memory and BM25 search, helping you build faster and add Stripe payments ...
Journal of Medical Internet Research

Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis

And meta-regression further revealed an evaluation in predictive accuracy in prospective study designs (regression coefficient=2.289, P=0.001). Conclusions: Unlike previous narrative reviews, this ...
IEEE

Predictive Coding of Spiking Neural Network in Continuous Time

Abstract: Predictive coding is a theory developed to explain how the brain predicts statistical regularities present in nature and eliminates redundant stimuli between cortical layers. A common method ...