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Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach.
Chen, Toly; Wang, Yu-Cheng.
  • Chen T; Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, University Road, Hsinchu 1001, Taiwan.
  • Wang YC; Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung 41349, Taiwan.
Healthcare (Basel) ; 9(11)2021 Oct 28.
Article in English | MEDLINE | ID: covidwho-1488531
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Topics: Vaccines Language: English Year: 2021 Document Type: Article Affiliation country: Healthcare9111461

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Topics: Vaccines Language: English Year: 2021 Document Type: Article Affiliation country: Healthcare9111461