AIMC Topic: Time Factors

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Neural-network-based accelerated safe Q-learning for optimal control of discrete-time nonlinear systems with state constraints.

Neural networks : the official journal of the International Neural Network Society Feb 10, 2025
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...
Time Factors Nonlinear Dynamics Algorithms Learning Humans Neural Networks, Computer Machine Learning
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Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

Circulation. Arrhythmia and electrophysiology Feb 10, 2025
BACKGROUND: It is difficult to identify patients with atrial fibrillation (AF) most likely to respond to ablation. While any arrhythmia patient may recur after acutely successful ablation, AF is unusual in that patients may have long-term arrhythmia ...
Aged Male Middle Aged Time Factors Electrocardiography Treatment Outcome Machine Learning Phenotype Female Humans Atrial Fibrillation Action Potentials Heart Rate Predictive Value of Tests Electrophysiologic Techniques, Cardiac Catheter Ablation Registries
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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

Cardiovascular diabetology Feb 7, 2025
BACKGROUND: Cardiovascular complications are major concerns for Chinese patients with type 2 diabetes. Accurately predicting these risks remains challenging due to limitations in traditional risk models. We aimed to develop a dynamic prediction model...
Time Factors Diabetes Mellitus, Type 2 East Asian People Risk Assessment China Predictive Value of Tests Heart Disease Risk Factors Female Reproducibility of Results Aged Male Cardiovascular Diseases Middle Aged Machine Learning Decision Support Techniques Prognosis Humans
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GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series.

Neural networks : the official journal of the International Neural Network Society Feb 5, 2025
Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with type 1 or 2 diabetes, thereby reducing complications and improving quality of life. The state of the art of BG prediction has been ac...
Humans Time Factors Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1 Neural Networks, Computer Recurrent Neural Networks Deep Learning Blood Glucose
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Fast In Vivo Two-Photon Fluorescence Imaging via Lateral and Axial Resolution Restoration With Self-Supervised Learning.

Journal of biophotonics Feb 5, 2025
Two-photon fluorescence (TPF) imaging opens a new avenue to achieve high resolution at extended penetration depths. However, it is difficult for conventional TPF imaging systems to simultaneously achieve high resolution and speed. In this work, we de...
Deep Learning Time Factors Image Processing, Computer-Assisted Animals Signal-To-Noise Ratio Optical Imaging Microscopy, Fluorescence, Multiphoton Mice Supervised Machine Learning
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Fast finite-time quantized control of multi-layer networks and its applications in secure communication.

Neural networks : the official journal of the International Neural Network Society Feb 4, 2025
This paper introduces a quantized controller to address the challenge of fast finite-time synchronization of multi-layer networks, where each layer represents a distinct type of interaction within complex systems. Firstly, based on the stability theo...
Computer Security Neural Networks, Computer Computer Simulation Algorithms Communication Time Factors
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FxTS-Net: Fixed-time stable learning framework for Neural ODEs.

Neural networks : the official journal of the International Neural Network Society Feb 1, 2025
Neural Ordinary Differential Equations (Neural ODEs), as a novel category of modeling big data methods, cleverly link traditional neural networks and dynamical systems. However, it is challenging to ensure the dynamics system reaches a correctly pred...
Time Factors Humans Neural Networks, Computer Machine Learning Algorithms Computer Simulation Learning
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Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience Feb 1, 2025
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...
Animals Time Factors Models, Neurological Humans Neural Networks, Computer Conditioning, Classical Time Perception Discrimination, Psychological Action Potentials Neurons Nerve Net
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COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation.

Neural networks : the official journal of the International Neural Network Society Jan 31, 2025
Current research on next point-of-interest (POI) recommendation focuses on capturing users' behavior patterns residing in their mobility trajectories. However, the learning process will inevitably cause discrepancies between the recommendation and in...
Time Factors Humans Neural Networks, Computer
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Synergistic modeling of hemorrhagic dengue fever: Passive immunity dynamics and time-delay neural network analysis.

Computational biology and chemistry Jan 31, 2025
Dengue fever poses a formidable epidemiological challenge, particularly for vulnerable groups such as infants. This research paper establishes a mathematical model to describe the dynamics of secondary immunity in infants against dengue hemorrhagic f...
Infant Time Factors Severe Dengue Humans Neural Networks, Computer
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