Enhancing Small Medical Dataset Classification Performance Using GAN
Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to enhance the classifier’s generalization performance...
Main Authors: | Mohammad Alauthman, Ahmad Al-qerem, Bilal Sowan, Ayoub Alsarhan, Mohammed Eshtay, Amjad Aldweesh, Nauman Aslam |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Informatics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9709/10/1/28 |
Similar Items
-
Tabular Data Generation to Improve Classification of Liver Disease Diagnosis
by: Mohammad Alauthman, et al.
Published: (2023-02-01) -
LSUN-Stanford Car Dataset: Enhancing Large-Scale Car Image Datasets Using Deep Learning for Usage in GAN Training
by: Tin Kramberger, et al.
Published: (2020-07-01) -
A Comparative Analysis of the Novel Conditional Deep Convolutional Neural Network Model, Using Conditional Deep Convolutional Generative Adversarial Network-Generated Synthetic and Augmented Brain Tumor Datasets for Image Classification
by: Efe Precious Onakpojeruo, et al.
Published: (2024-05-01) -
Improving Cancer Detection Classification Performance Using GANs in Breast Cancer Data
by: Emilija Strelcenia, et al.
Published: (2023-01-01) -
Development of brain tumor radiogenomic classification using GAN-based augmentation of MRI slices in the newly released gazi brains dataset
by: M.M.Enes Yurtsever, et al.
Published: (2024-10-01)