Building the hospital intelligent twins for all-scenario intelligence health care
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 20552076221107894 |
Journal / Publication | Digital Health |
Volume | 8 |
Online published | 12 Jun 2022 |
Publication status | Published - 2022 |
Link(s)
DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85132285569&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(1b42ed4d-8072-4078-856b-d69fdd176f02).html |
Abstract
The COVID-19 pandemic has accelerated a long-term trend of smart hospital development. However, there is no consistent conceptualization of what a smart hospital entails. Few hospitals have genuinely reached being "smart," primarily failing to bring systems together and consider implications from all perspectives. Hospital Intelligent Twins, a new technology integration powered by IoT, AI, cloud computing, and 5G application to create all-scenario intelligence for health care and hospital management. This communication presented a smart hospital for all-scenario intelligence by creating the hospital Intelligent Twins. Intelligent Twins is widely involved in medical activities. However, solving the medical ethics, protecting patient privacy, and reducing security risks involved are significant challenges for all-scenario intelligence applications. This exploration of creating hospital Intelligent Twins that can be a worthwhile endeavor to assess how to inform evidence-based decision-making better and enhance patient satisfaction and outcomes.
Research Area(s)
- Smart hospital, intelligent twins, digital twins, all-scenario intelligence, China
Citation Format(s)
Building the hospital intelligent twins for all-scenario intelligence health care. / Cheng, Weibin; Lian, Wanmin; Tian, Junzhang.
In: Digital Health, Vol. 8, 20552076221107894, 2022.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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