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  • [\'Department 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. Electronic address: mloey@fci.bu.edu.eg.\', \'Department of Information Systems, Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13518, Egypt; Faculty of Computer Science and Engineering, Galala University, Suez 435611, Egypt. Electronic address: shaker.elsappagh@gu.edu.eg.\', \'Center for Artificial Intelligence Research and Optimization, Torrens University Australia, Fortitude Valley, Brisbane, QLD, 4006, Australia; Yonsei Frontier Lab, Yonsei University, Seoul, South Korea. Electronic address: ali.mirjalili@gmail.com.\']
?:citedBy
  • -1
?:creator
?:doi
?:doi
  • S0010-4825(22)00005-110.1016/j.compbiomed.2022.105213
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  • Computers in biology and medicine
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?:pmid
  • 35026573
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  • 68
?:title
  • Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.
?:type
?:year
  • 2022

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