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Efficient anomaly detection from medical signals and images with convolutional neural networks for Internet of medical things (IoMT) systems.

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第一作者: Ali A,Khalil
第一单位: Department of Electronics and Communications, Faculty of Engineering, Minia University, Minia, Egypt.
作者单位: Department of Electronics and Communications, Faculty of Engineering, Minia University, Minia, Egypt. [1] Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt. [2] Engineering Department, Nuclear Research Center, Atomic Energy Authority, Cairo, Egypt. [3] Department of the Robotics and Intelligent Machines, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt. [4] Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.;University of Cassino and Southern Lazio, Italy. [5] Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt. [6] Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 84428, Riyadh 11671, Saudi Arabia. [7] Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, UK. [8] Department of Electronics Technology, Faculty of Technology and Education, Helwan University, Cairo, Egypt. [9] Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.;Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 84428, Riyadh 11671, Saudi Arabia. [10]
DOI 10.1002/cnm.3530
PMID 34506081
发布时间 2022-04-05
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International journal for numerical methods in biomedical engineering

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