Publications by authors named "Aseel Smerat"
Nerve signal conduction, and particularly in myelinated nerve fibers, is a highly dynamic phenomenon that is affected by various biological and physical factors. The propagation of such moving electric signals may seemingly help elucidate the mechanisms underlying normal and abnormal functioning. This work aims to derive the exact physical wave solutions of the nonlinear partial differential equations with fractional beta-derivatives for the cases of transmission of nerve impulses in coupled nerves.
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- Advancements in AI and ML are transforming the medical field, enhancing patient care and disease modeling, but challenges like data variability and class imbalance hinder optimal predictive performance.
- A new AI framework combining Gradient Boosting Machines and Deep Neural Networks was tested on two datasets, showing better results in accuracy metrics compared to traditional models, including achieving an AUROC of 0.96 on the UK Biobank dataset.
- The framework not only demonstrated superior accuracy but also trained quickly, making it well-suited for real-time clinical applications, with future enhancements aimed at improving scalability and interpretability for broader use.
In recent times, there has been notable progress in control systems across various industrial domains, necessitating effective management of dynamic systems for optimal functionality. A crucial research focus has emerged in optimizing control parameters to augment controller performance. Among the plethora of optimization algorithms, the mountain gazelle optimizer (MGO) stands out for its capacity to emulate the agile movements and behavioral strategies observed in mountain gazelles.
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