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  • [\'Department of Mechanical Engineering, Khalifa University, Abu Dhabi, UAE.\', \'System on Chip Center (SOCC), Khalifa University, Abu Dhabi, UAE.\', \'Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi, UAE.\', \'Center for Cyber-Physical Systems (C2PS), EECS Department, Khalifa University, Abu Dhabi, UAE.\', \'Center for Biotechnology (BTC), Khalifa University, Abu Dhabi, UAE.\', \'College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, UAE.\', \'Department of Mechanical Engineering, Khalifa University, Abu Dhabi, UAE. anas.alazzam@ku.ac.ae.\', \'System on Chip Center (SOCC), Khalifa University, Abu Dhabi, UAE. anas.alazzam@ku.ac.ae.\']
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  • -1
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?:doi
  • 10.1038/s41598-022-07954-2
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  • Scientific reports
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  • 35260715
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  • 1.533
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  • 122
?:title
  • A deep learning-driven low-power, accurate, and portable platform for rapid detection of COVID-19 using reverse-transcription loop-mediated isothermal amplification.
?:type
?:year
  • 2022

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