Background Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study ...
This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
An in-depth look at how Mikaela Stenmo merges statistical analysis with creative execution to redefine experiential ...
Abstract: This study presents a novel model predictive current control (MPCC) strategy for an interior permanent magnet synchronous motor (IPMSM) drive. The proposed MPCC integrates a sliding mode ...
This studentship will develop physics-informed Edge AI methods for predictive health management of batteries and power electronics in electrified vehicles under real-world driving conditions.
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 a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
Postpartum depression (PPD) is a prevalent mental health condition that significantly impacts the wellbeing of mothers and their families. Early identification of high-risk women continues to be a ...
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