AIMC Topic: Time Factors

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Insights into the temporal dynamics of identifying problem gambling on an online casino: A machine learning study on routinely collected individual account data.

Journal of behavioral addictions Feb 27, 2025
BACKGROUND AND AIMS: The digitalization of gambling provides unprecedented opportunities for early identification of problem gambling, a well-recognized public health issue. This study aimed to advance current practices by employing advanced machine ...
Gambling Time Factors Internet Machine Learning Humans Female Sweden Adult Male
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Prediction of sarcopenia at different time intervals: an interpretable machine learning analysis of modifiable factors.

BMC geriatrics Feb 27, 2025
OBJECTIVES: This study aims to develop sarcopenia risk prediction models for Chinese older adults at different time intervals and to identify and compare modifiable factors contributing to sarcopenia development.
Male Middle Aged Risk Assessment Longitudinal Studies Risk Factors Machine Learning Sarcopenia Aged Female Predictive Value of Tests Humans China Time Factors
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Data-efficient generalization of AI transformers for noise reduction in ultra-fast lung PET scans.

European journal of nuclear medicine and molecular imaging Feb 26, 2025
PURPOSE: Respiratory motion during PET acquisition may produce lesion blurring. Ultra-fast 20-second breath-hold (U2BH) PET reduces respiratory motion artifacts, but the shortened scanning time increases statistical noise and may affect diagnostic qu...
Lung Deep Learning Time Factors Humans Artifacts Positron Emission Tomography Computed Tomography Signal-To-Noise Ratio Positron-Emission Tomography Breath Holding Image Processing, Computer-Assisted
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Exploring temporal information dynamics in Spiking Neural Networks: Fast Temporal Efficient Training.

Journal of neuroscience methods Feb 25, 2025
BACKGROUND: Spiking Neural Networks (SNNs) hold significant potential in brain simulation and temporal data processing. While recent research has focused on developing neuron models and leveraging temporal dynamics to enhance performance, there is a ...
Models, Neurological Action Potentials Neurons Algorithms Brain Time Factors Humans Neural Networks, Computer
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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

Computer assisted surgery (Abingdon, England) Feb 24, 2025
This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). We employed only the clinical phases derived from video analysis as input to ...
Algorithms Deep Learning Time Factors Humans Cardiac Catheterization Workflow Benchmarking
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Neural-network-based practical specified-time resilient formation maneuver control for second-order nonlinear multi-robot systems under FDI attacks.

Neural networks : the official journal of the International Neural Network Society Feb 22, 2025
This paper presents a specified-time resilient formation maneuver control approach for second-order nonlinear multi-robot systems under false data injection (FDI) attacks, incorporating an offline neural network. Building on existing works in integra...
Nonlinear Dynamics Computer Simulation Neural Networks, Computer Time Factors Computer Security Algorithms Robotics
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A strictly predefined-time convergent and anti-noise fractional-order zeroing neural network for solving time-variant quadratic programming in kinematic robot control.

Neural networks : the official journal of the International Neural Network Society Feb 22, 2025
This paper proposes a strictly predefined-time convergent and anti-noise fractional-order zeroing neural network (SPTC-AN-FOZNN) model, meticulously designed for addressing time-variant quadratic programming (TVQP) problems. This model marks the firs...
Algorithms Computer Simulation Time Factors Robotics Biomechanical Phenomena Humans Neural Networks, Computer
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Self-triggered neural tracking control for discrete-time nonlinear systems via adaptive critic learning.

Neural networks : the official journal of the International Neural Network Society Feb 21, 2025
In this paper, a novel self-triggered optimal tracking control method is developed based on the online action-critic technique for discrete-time nonlinear systems. First, an augmented plant is constructed by integrating the system state with the refe...
Humans Neural Networks, Computer Learning Time Factors Nonlinear Dynamics Machine Learning Algorithms
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A Multi-objective transfer learning framework for time series forecasting with Concept Echo State Networks.

Neural networks : the official journal of the International Neural Network Society Feb 20, 2025
This paper introduces a novel transfer learning framework for time series forecasting that uses Concept Echo State Network (CESN) and a multi-objective optimization strategy. Our approach addresses the challenges of feature extraction and knowledge t...
Machine Learning Algorithms Forecasting Humans Neural Networks, Computer Time Factors
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AI-Driven Analysis of Drug Marketing Efficiency: Unveiling FDA Approval to Market Release Dynamics.

The AAPS journal Feb 20, 2025
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...
Marketing Time Factors Humans Drug Industry United States Drug Approval Artificial Intelligence United States Food and Drug Administration
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