AI-enabled research tools can accelerate health research, but their data-science roots may clash with epidemiological ...

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 ...

Public experiment log using Get Physics Done (GPD) with Codex to explore predictive control of tokamak plasma turbulence and confinement. A physics-based flight simulator for optimizing airbrake ...

Marc Santos is a Guides Staff Writer from the Philippines with a BA in Communication Arts and over six years of experience in writing gaming news and guides. He plays just about everything, from ...

Abstract: Model-free predictive control (MFPC) has become a popular choice for addressing the robustness limitations of model-based predictive control (MBPC), by replacing physical models with ...

In 2024, almost 70% of all U.S. hospitals were using predictive artificial intelligence, the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT revealed in its ...

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control and ...

Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the potential risks to patients and call for improved governance to ensure the ...