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Time Factors

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Long-duration electrocardiogram classification based on Subspace Search VMD and Fourier Pooling Broad Learning System.

Medical engineering & physics
Detecting early stages of cardiovascular disease from short-duration Electrocardiogram (ECG) signals is challenging. However, long-duration ECG data are susceptible to various types of noise during acquisition. To tackle the problem, Subspace Search ...

COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation.

Neural networks : the official journal of the International Neural Network Society
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...

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
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...

Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

Circulation. Arrhythmia and electrophysiology
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 ...

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
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...

Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

Cardiovascular diabetology
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...

Network Delay Forecast and Master-Slave Consistency Enhancement for Remote Surgical Robots.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The inevitable network delay can directly impact the process of remote surgeries and affect the master-slave motion consistency, and sudden changes in delay can compromise surgical safety.

Fast In Vivo Two-Photon Fluorescence Imaging via Lateral and Axial Resolution Restoration With Self-Supervised Learning.

Journal of biophotonics
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...

FxTS-Net: Fixed-time stable learning framework for Neural ODEs.

Neural networks : the official journal of the International Neural Network Society
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...

Exploring the Influence of Feature Selection Methods on a Random Forest Model for Gait Time Series Prediction Using Inertial Measurement Units.

Journal of biomechanical engineering
Despite the increasing use of inertial measurement units (IMUs) and machine learning techniques for gait analysis, there remains a gap in which feature selection methods are best tailored for gait time series prediction. This study explores the impac...