Deep Hybrid Learning Approaches for COVID-19 Virus Detection Using Chest X-ray Images

被引:0
|
作者
Alohali, Mansor [1 ]
机构
[1] Imam Mohammad Ibn Saud Islamic Univ IMSIU, Appl Coll, Riyadh, Saudi Arabia
关键词
COVID-19; detection; deep learning; deep hybrid learning; chest X-ray analysis; machine learning classifiers; medical image analysis; convolutional networks;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper introduces a novel deep learning framework for highly accurate COVID-19 detection using chest X-ray images. The proposed model tackles the challenge by combining stacked Convolutional Neural Network models for superior feature extraction to potentially enhance interpretability. The proposed model achieved a high accuracy in distinguishing COVID-19 from healthy cases. The study demonstrates the potential of deep hybrid learning for accurate COVID-19 detection, paving the way for its application in real- world settings. Future research directions could explore methods to further refine the model's capabilities. Overall, this work contributes significantly to the development of robust deep- learning methods for COVID-19 detection with the potential for broader use in medical image analysis.
引用
收藏
页码:120 / 126
页数:7
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