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  • 标题:Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach
  • 本地全文:下载
  • 作者:Toly Chen ; Yu-Cheng Wang
  • 期刊名称:Healthcare
  • 电子版ISSN:2227-9032
  • 出版年度:2021
  • 卷号:9
  • 期号:11
  • DOI:10.3390/healthcare9111461
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:The COVID-19 pandemic seems to be entering its final stage. However, to restore normal life, the applications of smart technologies are still necessary. Therefore, this research is dedicated to exploring the applications of smart technologies that can support mobile healthcare after the COVID-19 pandemic. To this end, this study compares smart technology applications to support mobile healthcare within the COVID-19 pandemic with those before the pandemic, so as to estimate possible developments in this field. In addition, to quantitatively assess and compare smart technology applications that may support mobile healthcare after the COVID-19 pandemic, the calibrated fuzzy geometric mean (CFGM)-fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) approach is applied. The proposed methodology has been applied to evaluate and compare nine potential smart technology applications for supporting mobile healthcare after the COVID-19 pandemic. According to the experimental results, “vaccine passport and related applications” and “smart watches” were the most suitable smart technology applications for supporting mobile healthcare after the COVID-19 pandemic.
  • 关键词:smart technology; mobile healthcare; COVID-19 pandemic; calibrated fuzzy geometric mean; FTOPSIS
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