AIMC Topic: Recurrent Neural Networks

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The Impact of the COVID-19 Pandemic on Stock Market Performance in G20 Countries: Evidence from Long Short-Term Memory with a Recurrent Neural Network Approach.

Big data Dec 20, 2023
In light of developing and industrialized nations, the G20 economies account for a whopping two-thirds of the world's population and are the largest economies globally. Public emergencies have occasionally arisen due to the rapid spread of COVID-19 g...
Neural Networks, Computer Pandemics COVID-19 Humans Developing Countries Investments Recurrent Neural Networks SARS-CoV-2 China Saudi Arabia
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Automated atomic force microscopy analysis using convolutional and recurrent neural networks.

Biophysical journal Jun 17, 2025
Atomic force microscope (AFM) indentation allows high-resolution spatial characterization of biomechanical properties of cells and tissues. Rapid, reproducible, and quantitative analysis of AFM force curves has been challenging due to several technic...
Recurrent Neural Networks Algorithms Humans Microscopy, Atomic Force Neural Networks, Computer Automation
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BigLSTM: Recurrent neural network for the treatment of anomalous temporal signals. Application in the prediction of endotracheal obstruction in COVID-19 patients in the intensive care unit.

Computers in biology and medicine Jun 1, 2025
Real-world applications, particularly in the medical field, often handle irregular time signals (ITS) with non-uniform intervals between measurements. These irregularities arise due to missing data, inconsistent sampling frequencies, and multi-sensor...
Airway Obstruction Intensive Care Units Recurrent Neural Networks Female Humans SARS-CoV-2 Neural Networks, Computer Male COVID-19 Middle Aged Signal Processing, Computer-Assisted
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Development and validation of an integrated residual-recurrent neural network model for automated heart murmur detection in pediatric populations.

Scientific reports May 31, 2025
Congenital heart disease affects approximately 1% of children worldwide, with a number of cases in resource-limited settings remaining undiagnosed through school age. While cardiac auscultation is a key screening method, its effectiveness varies wide...
Sensitivity and Specificity Male Infant Neural Networks, Computer Female Child Heart Defects, Congenital Heart Auscultation Deep Learning Adolescent Child, Preschool Humans Heart Murmurs Recurrent Neural Networks
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PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks.

Journal of chemical information and modeling May 12, 2025
This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model relies on a recurrent neural network that was trained to decode embedded molecular fingerprints into SMI...
Bayes Theorem Ligands Small Molecule Libraries Receptors, Dopamine D2 Recurrent Neural Networks Neural Networks, Computer Drug Design
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Recurrent Neural Network/Machine Learning Predictions of Reactive Channels in H + CH at E = 30 eV: A Prototype of Ion Cancer Therapy Reactions.

Journal of computational chemistry Feb 15, 2025
We present a simplest-level electron nuclear dynamics/machine learning (SLEND/ML) approach to predict chemical properties in ion cancer therapy (ICT) reactions. SLEND is a time-dependent, variational, on-the-fly, and nonadiabatic method. In SLEND, nu...
Recurrent Neural Networks Humans Neural Networks, Computer Electrons Machine Learning Hydrogen Neoplasms
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Role of short-term plasticity and slow temporal dynamics in enhancing time series prediction with a brain-inspired recurrent neural network.

Chaos (Woodbury, N.Y.) Feb 1, 2025
Typical reservoir networks are based on random connectivity patterns that differ from brain circuits in two important ways. First, traditional reservoir networks lack synaptic plasticity among recurrent units, whereas cortical networks exhibit plasti...
Nerve Net Recurrent Neural Networks Time Factors Humans Neuronal Plasticity Neural Networks, Computer Models, Neurological Brain
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iACVP-MR: Accurate Identification of Anti-coronavirus Peptide based on Multiple Features Information and Recurrent Neural Network.

Current medicinal chemistry Jan 1, 2025
BACKGROUND: Over the years, viruses have caused human illness and threatened human health. Therefore, it is pressing to develop anti-coronavirus infection drugs with clear function, low cost, and high safety. Anti-coronavirus peptide (ACVP) is a key ...
Humans Neural Networks, Computer Peptides Antiviral Agents Coronavirus Recurrent Neural Networks
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Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by fluctuating plaque surfaces with blood flow pulsation, is a dynamic characteristic of these plaques that has recently attracted attention. Detecting ...
Plaque, Atherosclerotic Humans Carotid Stenosis Neural Networks, Computer Recurrent Neural Networks Algorithms Image Processing, Computer-Assisted Deep Learning Carotid Arteries Ultrasonography
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A Regression Framework for Predicting Cognitive Decline in Frontotemporal Dementia using Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder with a diverse range of symptoms, including personality changes, behavioral disturbances, language deficits, and impaired executive functions. FTD has three main subtypes: beha...
Frontotemporal Dementia Neuropsychological Tests Recurrent Neural Networks Cognitive Dysfunction Regression Analysis Aged Male Humans Middle Aged Neural Networks, Computer Female
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