AIMC Topic: Generative Adversarial Networks

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Principal component conditional generative adversarial networks for imbalanced ECG classification enhancement.

PloS one Aug 22, 2025
With over a century of development, electrocardiogram (ECG) diagnostics has become the preferred tool for healthcare professionals in cardiovascular disease diagnosis and monitoring. As wearable devices and mobile monitoring technologies become wides...
Humans Neural Networks, Computer Principal Component Analysis Signal Processing, Computer-Assisted Generative Adversarial Networks Algorithms Electrocardiography
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Thyroid disease classification using generative adversarial networks and Kolmogorov-Arnold network for three-class classification.

BMC medical informatics and decision making Jul 31, 2025
Thyroid disease classification is a critical challenge in medical diagnostics, requiring accurate differentiation between hyperthyroidism, hypothyroidism, and normal thyroid function. This study introduces an advanced machine learning approach that i...
Humans Neural Networks, Computer Machine Learning Thyroid Diseases Generative Adversarial Networks
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Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.

Neuroinformatics Jul 10, 2025
Non-invasive intracranial pressure (ICP) monitoring can help clinicians safely and efficiently monitor spaceflight-associated neuro-ocular syndrome (SANS), idiopathic intracranial hypertension, and traumatic brain injury in astronauts. Current invasi...
Humans Cerebrospinal Fluid Pressure Cell-Free Nucleic Acids Neural Networks, Computer Generative Adversarial Networks Biomarkers
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A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.

BMC medical informatics and decision making Jul 10, 2025
BACKGROUND: Intradialytic Hypotension (IDH) is a frequent complication in hemodialysis, yet predictive modeling is challenged by class imbalance. Traditional oversampling methods often struggle with complex clinical data. This study evaluates an enha...
Aged Male Neural Networks, Computer Female Hypotension Generative Adversarial Networks Middle Aged Renal Dialysis Humans
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Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention.

Scientific reports Jul 1, 2025
Since 3D medical imaging data is a string of sequential images, there is a strong correlation between consecutive images. Deep convolutional networks perform well in extracting spatial features, but are less capable for processing sequence data compa...
Attention Image Processing, Computer-Assisted Generative Adversarial Networks Humans Memory, Short-Term Algorithms Neural Networks, Computer Imaging, Three-Dimensional
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A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Scientific reports Jul 1, 2025
Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to assist in diagnosis. We have constructed a new method called ACWGAN by combining ACGAN and WGAN methods for data augmentation to to enhance the data of ...
Venous Thrombosis Stroke Generative Adversarial Networks Middle Aged Deep Learning Aged Neural Networks, Computer Male Female Humans
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Systematic review of generative adversarial networks (GANs) in cell microscopy: Trends, practices, and impact on image augmentation.

PloS one Jun 24, 2025
Cell microscopy is the main tool that allows researchers to study microorganisms and plays a key role in observing and understanding the morphology, interactions, and development of microorganisms. However, there exist limitations in both the techniq...
Microscopy Generative Adversarial Networks Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Circular saw blade wear status prediction based on generative adversarial network and CNN-LSTM model.

PloS one Jun 18, 2025
Monitoring the status of circular saw blades is an effective measure to ensure the production efficiency and safety of spent fuel assembly cutting. However, the prediction of wear during the cutting of stainless steel shells of spent fuel assemblies ...
Neural Networks, Computer Stainless Steel Generative Adversarial Networks Algorithms Models, Theoretical
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Towards large nuclear imaging system optical simulations with optiGAN, a generative adversarial network.

Physics in medicine and biology Jun 9, 2025
Optical Monte Carlo (MC) simulations are essential for modeling light transport in radiation detectors used in nuclear imaging and high-energy physics. However, full-system simulations remain computationally prohibitive due to the need to track optic...
Generative Adversarial Networks Monte Carlo Method Photons Neural Networks, Computer Image Processing, Computer-Assisted
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High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks.

Scientific reports May 26, 2025
Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequences to enhance immunotherapy predictability and efficacy. The most variable and crucial part of the TCR receptor is the CDR3 sequence region. Current m...
Complementarity Determining Regions Computer Simulation Humans Generative Adversarial Networks Receptors, Antigen, T-Cell Neural Networks, Computer
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