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  • 标题:No title
  • 本地全文:下载
  • 作者:Mazin Abed Mohammed ; Seifedine Kadry ; Oana Geman
  • 期刊名称:Acta Informatica Pragensia
  • 电子版ISSN:1805-4951
  • 出版年度:2022
  • 卷号:11
  • 期号:1
  • 页码:141-144
  • DOI:10.18267/j.aip.175
  • 语种:Czech
  • 出版社:University of Economics, Prague
  • 摘要:The main objective of this special issue is to bring together diverse, novel and impactful research work on explainable deep learning for medicine based on the Internet of Medical Things, thereby accelerating research in this field. The regulation of Internet of Medical Things (IoMT) aware industrial networks for medical science applications has been evolving day by day. An IoMT industrial network consists of different bio-medical sensors, wireless technologies and cloud computing services to run different healthcare applications. However, IoMT industrial networks also suffer from dynamics uncertainties, such as intermittent changes in wireless network values, availability of cloud services and security issues, and require flexible systems to cope with these challenges for healthcare applications in the network.
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