AIMC Topic: Generative Adversarial Networks

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

PloS one
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...

Prediction of hematoma changes in spontaneous intracerebral hemorrhage using a Transformer-based generative adversarial network to generate follow-up CT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PURPOSE: To visualize and assess hematoma growth trends by generating follow-up CT images within 24 h based on baseline CT images of spontaneous intracerebral hemorrhage (sICH) using Transformer-integrated Generative Adversarial Networks (GAN).

Thyroid disease classification using generative adversarial networks and Kolmogorov-Arnold network for three-class classification.

BMC medical informatics and decision making
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...

Automatic generation and risk stratification of carotid plaque in virtual shear wave elastography using a generative adversarial network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Shear wave elastography (SWE) is an effective ultrasound imaging technique for assessing carotid plaque vulnerability. However, acquiring SWE images typically requires costly specialized equipment and must be performed by experienced radiologists, wh...

Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.

Neuroinformatics
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...

A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.

BMC medical informatics and decision making
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...

Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention.

Scientific reports
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...

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Scientific reports
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 ...

A Innovative Strategy for Identifying Subtypes Through the Analysis of Multi-Omics Data with Adversarial Autoencoders.

Journal of computational biology : a journal of computational molecular cell biology
Cancer is a disease that is both complex and diverse, and effective diagnosis and treatment require an accurate depiction of tumor subtypes. Traditional methods of cancer identification, which rely on clinical and histopathological criteria, have lim...

Systematic review of generative adversarial networks (GANs) in cell microscopy: Trends, practices, and impact on image augmentation.

PloS one
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...