AIMC Topic: Recurrent Neural Networks

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Exploring a digital music teaching model integrated with recurrent neural networks under artificial intelligence.

Scientific reports Mar 3, 2025
This study proposes an intelligent digital music teaching model based on Artificial Intelligence (AI) and Long Short-Term Memory (LSTM) networks to enhance personalized assessment and feedback in music education. Within this teaching model, the music...
Teaching Recurrent Neural Networks Male Music Humans Artificial Intelligence Female Neural Networks, Computer
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Complex-Valued Convolutional Gated Recurrent Neural Network for Ultrasound Beamforming.

IEEE transactions on neural networks and learning systems Feb 28, 2025
Ultrasound detection is a potent tool for the clinical diagnosis of various diseases due to its real-time, convenient, and noninvasive qualities. Yet, existing ultrasound beamforming and related methods face a big challenge to improve both the qualit...
Humans Neural Networks, Computer Recurrent Neural Networks Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Algorithms Ultrasonography
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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...
Blood Glucose Time Factors Neural Networks, Computer Deep Learning Recurrent Neural Networks Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1 Humans
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Recurrent neural networks with transient trajectory explain working memory encoding mechanisms.

Communications biology Jan 28, 2025
Whether working memory (WM) is encoded by persistent activity using attractors or by dynamic activity using transient trajectories has been debated for decades in both experimental and modeling studies, and a consensus has not been reached. Even thou...
Nerve Net Recurrent Neural Networks Humans Neural Networks, Computer Models, Neurological Animals Memory, Short-Term
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Comparative Analysis of Recurrent Neural Networks with Conjoint Fingerprints for Skin Corrosion Prediction.

Journal of chemical information and modeling Jan 21, 2025
Skin corrosion assessment is an essential toxicity end point that addresses safety concerns for topical dosage forms and cosmetic products. Previously, skin corrosion assessments required animal testing; however, differences in skin architecture and ...
Deep Learning Skin Recurrent Neural Networks Corrosion Humans Neural Networks, Computer
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Chaotic recurrent neural networks for brain modelling: A review.

Neural networks : the official journal of the International Neural Network Society Dec 27, 2024
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...
Nonlinear Dynamics Humans Recurrent Neural Networks Computer Simulation Neural Networks, Computer Algorithms Animals Models, Neurological Brain
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Performance of recurrent neural networks with Monte Carlo dropout for predicting pharmacokinetic parameters from dynamic contrast-enhanced magnetic resonance imaging data.

Journal of applied clinical medical physics Dec 23, 2024
PURPOSE: To quantitatively evaluate the performance of two types of recurrent neural networks (RNNs), long short-term memory (LSTM) and gated recurrent units (GRU), using Monte Carlo dropout (MCD) to predict pharmacokinetic (PK) parameters from dynam...
Algorithms Computer Simulation Image Processing, Computer-Assisted Contrast Media Brain Neoplasms Humans Neural Networks, Computer Monte Carlo Method Magnetic Resonance Imaging Recurrent Neural Networks Radiotherapy Planning, Computer-Assisted
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Revisiting the problem of learning long-term dependencies in recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 26, 2024
Recurrent neural networks (RNNs) are an important class of models for learning sequential behavior. However, training RNNs to learn long-term dependencies is a tremendously difficult task, and this difficulty is widely attributed to the vanishing and...
Learning Humans Recurrent Neural Networks Neural Networks, Computer
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BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation.

Journal of computational biology : a journal of computational molecular cell biology Jul 25, 2024
Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event types, is crucial for understanding adverse drug reactions and drug combinations. This work introduces a Bidirectional Recurrent Neural Network model for DDI ev...
Drug Interactions Recurrent Neural Networks Algorithms Computational Biology Humans Neural Networks, Computer
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Identification and segregation of genes with improved recurrent neural network trained with optimal gene level and mutation level features.

Computer methods in biomechanics and biomedical engineering Feb 29, 2024
Even though many different approaches have been employed to address the complex mutational heterogeneity of cancer, finding driver genes is still problematic since other genomic factors cannot be fully integrated for combined analyses. This research ...
Algorithms Mutation Humans Recurrent Neural Networks Neural Networks, Computer
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