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Published on: December 19, 2020
Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data
Mohamed Loey1, Shaker El-Sappagh2, Seyedali Mirjalili3
1Department of Computer Science, Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13518, Egypt; Information Technology Program, New Cairo Technological University, New Cairo, Egypt; Computer Engineering Department, Cybersecurity Department, Engineering and Information Technology College, Buraydah Colleges, Buraydah, Al-Qassim, Saudi Arabia.
A new Bayesian optimization-based Convolutional Neural Network (CNN) model accurately identifies Coronavirus Disease 2019 (COVID-19) from chest X-rays. This deep learning approach achieved 96% accuracy, offering a reliable tool for rapid COVID-19 diagnosis.
Area of Science:
- Artificial Intelligence
- Medical Imaging
- Deep Learning
Background:
- Coronavirus Disease 2019 (COVID-19) is a highly contagious global pandemic.
- Accurate and rapid patient identification is crucial for disease control.
- Deep learning shows significant potential in medical image analysis.
Purpose of the Study:
- To develop and evaluate a novel deep learning model for classifying COVID-19 chest X-ray images.
- To improve the accuracy of COVID-19 detection in diverse real-world scenarios.
Main Methods:
- A Convolutional Neural Network (CNN) model was designed to extract deep features from chest X-ray images.
- Bayesian optimization was employed to fine-tune CNN hyperparameters for optimal performance.
- A large dataset of 10,848 chest X-ray images (COVID-19, normal, and pneumonia) was utilized.
Main Results:
- The proposed Bayesian optimization-based CNN model achieved 96% accuracy in classifying COVID-19 chest X-ray images.
- Ablation studies confirmed the effectiveness of the Bayesian optimization approach compared to other scenarios.
- The model demonstrated high trustworthiness and accuracy in real-world application.
Conclusions:
- The novel Bayesian optimization-CNN model offers a highly accurate and reliable method for COVID-19 detection using chest X-rays.
- This deep learning approach can significantly aid in the rapid and precise identification of COVID-19 patients.
- The model's performance suggests its potential for integration into clinical diagnostic workflows.
