Data Augmentation Based on Generative Adversarial Networks to Improve Stage Classification of Chronic Kidney Disease
The prevalence of chronic kidney disease (CKD) is estimated to be 13.4% worldwide and 15% in the United States. CKD has been recognized as a leading public health problem worldwide. Unfortunately, as many as 90% of CKD patients do not know that they already have CKD. Ultrasonography is usually the f...
Main Authors: | Yun-Te Liao, Chien-Hung Lee, Kuo-Su Chen, Chie-Pein Chen, Tun-Wen Pai |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/1/352 |
Similar Items
-
Improving the IoT Attack Classification Mechanism with Data Augmentation for Generative Adversarial Networks
by: Hung-Chi Chu, et al.
Published: (2023-11-01) -
Automatic Kidney Segmentation Method Based on an Enhanced Generative Adversarial Network
by: Tian Shan, et al.
Published: (2023-04-01) -
Generative-Adversarial-Network-Based Data Augmentation for the Classification of Craniosynostosis
by: Kaiser Christian, et al.
Published: (2022-09-01) -
Augmenting image data using generative adversarial networks (GAN)
by: Liu, Xinchi
Published: (2024) -
Universal Adversarial Training Using Auxiliary Conditional Generative Model-Based Adversarial Attack Generation
by: Hiskias Dingeto, et al.
Published: (2023-07-01)