Neural networks : the official journal of the International Neural Network Society
39987713
Electricity is generated through various resources and then flows between regions via a complex system (grid). Imbalances in electricity generation can lead to the waste of renewable energy. As renewable energy is becoming a larger part of the grid, ...
Neural networks : the official journal of the International Neural Network Society
39987711
In recent years, deep correlation filters have demonstrated outstanding performance in robust object tracking. Nevertheless, the correlation filters encounter challenges in managing huge occlusion, target deviation, and background clutter due to the ...
This paper explores a novel approach using generative AI to enhance drug marketing strategies in the US pharmaceutical sector. By leveraging an official dataset sourced from the US government, the AI generates Python code to analyze the time interval...
Typical reservoir networks are based on random connectivity patterns that differ from brain circuits in two important ways. First, traditional reservoir networks lack synaptic plasticity among recurrent units, whereas cortical networks exhibit plasti...
The integration of paper-based microfluidics with deep learning represents a pivotal trend in enhancing diagnostic capabilities. This paper introduces a new approach to improve the performance of a paper-based microfluidic enzyme-linked immunosorbent...
Neural networks : the official journal of the International Neural Network Society
39955958
This article presents the master-slave time-delayed competitive neural networks in space-time discretized frames(STD-CNNs) with the heterogeneous structure, induced by the design of an adaptive learning parameter in the slave STD-CNNs. This article a...
Neural networks : the official journal of the International Neural Network Society
39955957
For unknown nonlinear systems with state constraints, it is difficult to achieve the safe optimal control by using Q-learning methods based on traditional quadratic utility functions. To solve this problem, this article proposes an accelerated safe Q...
BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationsh...
BACKGROUND: People living with diabetes mellitus (DM) and chronic kidney disease (CKD) are at significantly high risk of cardiovascular events (CVEs), however the predictive performance of traditional risk prediction methods are limited.
AIMS: Mortality risk after hospitalization for heart failure (HF) is high, especially in the first 90 days. This study aimed to construct a model automatically predicting 90 day post-discharge mortality using electronic health record (EHR) data 48 h ...