AI Medical Compendium Topic:
Time Factors

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Fixed-Time Synchronization of Competitive Neural Networks With Multiple Time Scales.

IEEE transactions on neural networks and learning systems
In this brief, we investigate the fixed-time synchronization of competitive neural networks with multiple time scales. These neural networks play an important role in visual processing, pattern recognition, neural computing, and so on. Our main contr...

Boundary Stabilization of Stochastic Delayed Cohen-Grossberg Neural Networks With Diffusion Terms.

IEEE transactions on neural networks and learning systems
This study considers the boundary stabilization for stochastic delayed Cohen-Grossberg neural networks (SDCGNNs) with diffusion terms by the Lyapunov functional method. In the realization of NNs, sometimes time delays and diffusion phenomenon cannot ...

Multivariate time-series classification with hierarchical variational graph pooling.

Neural networks : the official journal of the International Neural Network Society
In recent years, multivariate time-series classification (MTSC) has attracted considerable attention owing to the advancement of sensing technology. Existing deep-learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural ...

Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey.

Sensors (Basel, Switzerland)
Sensors are devices that output signals for sensing physical phenomena and are widely used in all aspects of our social production activities. The continuous recording of physical parameters allows effective analysis of the operational status of the ...

Fixed-time projective synchronization of delayed memristive neural networks via aperiodically semi-intermittent switching control.

ISA transactions
This paper studies the fixed-time projective synchronization problem for a class of delayed memristive neural networks via aperiodically semi-intermittent switching control. Instead of using the common traditional controller containing two power expo...

A Machine Learning Model for Predicting Mortality within 90 Days of Dialysis Initiation.

Kidney360
BACKGROUND: The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning-based tool for predicting mortality could inform patient-clinician shared decisio...

Quasisynchronization of Memristive Neural Networks With Communication Delays via Event-Triggered Impulsive Control.

IEEE transactions on cybernetics
This article considers the quasisynchronization of memristive neural networks (MNNs) with communication delays via event-triggered impulsive control (ETIC). In view of the limited communication and bandwidth, we adopt a novel switching event-triggere...

Short-Term Demand Forecast of E-Commerce Platform Based on ConvLSTM Network.

Computational intelligence and neuroscience
Based on real sales data, this article constructed LGBM and LSTM sales prediction models to compare and verify the performance of the proposed models. In this article, we forecast the product sales of stores in the future  + 3 days and use MAPE as th...

Validity of at-home rapid antigen lateral flow assay and artificial intelligence read to detect SARS-CoV-2.

Diagnostic microbiology and infectious disease
BACKGROUND: The gold standard for COVID-19 diagnosis-reverse-transcriptase polymerase chain reaction (RT-PCR)- is expensive and often slow to yield results whereas lateral flow tests can lack sensitivity.

Parameterized Luenberger-Type H State Estimator for Delayed Static Neural Networks.

IEEE transactions on neural networks and learning systems
This article proposes a new Luenberger-type state estimator that has parameterized observer gains dependent on the activation function, to improve the H state estimation performance of the static neural networks with time-varying delay. The nonlinear...