Generative adversarial networks in medical image augmentation: a review
Object With the development of deep learning, the number of training samples for medical
image-based diagnosis and treatment models is increasing. Generative Adversarial …
image-based diagnosis and treatment models is increasing. Generative Adversarial …
Deep learning approaches for data augmentation in medical imaging: a review
A Kebaili, J Lapuyade-Lahorgue, S Ruan - Journal of Imaging, 2023 - mdpi.com
Deep learning has become a popular tool for medical image analysis, but the limited
availability of training data remains a major challenge, particularly in the medical field where …
availability of training data remains a major challenge, particularly in the medical field where …
Synthetic data in machine learning for medicine and healthcare
Synthetic data in machine learning for medicine and healthcare | Nature Biomedical Engineering
Skip to main content Thank you for visiting nature.com. You are using a browser version with …
Skip to main content Thank you for visiting nature.com. You are using a browser version with …
Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework
As one of the representative unsupervised data augmentation methods, generative
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …
Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
COVID-19 patient health prediction using boosted random forest algorithm
Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time
collection, and processing of end-user devices is now in high demand. It is now superlative …
collection, and processing of end-user devices is now in high demand. It is now superlative …
Pneumonia classification using deep learning from chest X-ray images during COVID-19
The outbreak of the novel corona virus disease (COVID-19) in December 2019 has led to
global crisis around the world. The disease was declared pandemic by World Health …
global crisis around the world. The disease was declared pandemic by World Health …
[HTML][HTML] Machine learning and deep learning applications-a vision
The application of artificial intelligence is machine learning which is one of the current topics
in the computer field as well as for the new COVID-19 pandemic. Researchers have given a …
in the computer field as well as for the new COVID-19 pandemic. Researchers have given a …
A systematic review on data scarcity problem in deep learning: solution and applications
Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …
applications. Deep learning models require a large amount of data to train the model. In …
A novel medical diagnosis model for COVID-19 infection detection based on deep features and Bayesian optimization
A pneumonia of unknown causes, which was detected in Wuhan, China, and spread rapidly
throughout the world, was declared as Coronavirus disease 2019 (COVID-19). Thousands …
throughout the world, was declared as Coronavirus disease 2019 (COVID-19). Thousands …