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Smart healthcare: A prospective future medical approach for COVID-19

COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart healthcare solutions that address major requirements for coping with the COVID-19 pandemic, including (1) the continuous monitoring of severe acute respiratory syndrome coronavirus 2, (2) patient stratificat...

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Autores principales: Yang, De-Ming, Chang, Tai-Jay, Hung, Kai-Feng, Wang, Mong-Lien, Cheng, Yen-Fu, Chiang, Su-Hua, Chen, Mei-Fang, Liao, Yi-Ting, Lai, Wei-Qun, Liang, Kung-Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847685/
https://www.ncbi.nlm.nih.gov/pubmed/36227021
http://dx.doi.org/10.1097/JCMA.0000000000000824
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author Yang, De-Ming
Chang, Tai-Jay
Hung, Kai-Feng
Wang, Mong-Lien
Cheng, Yen-Fu
Chiang, Su-Hua
Chen, Mei-Fang
Liao, Yi-Ting
Lai, Wei-Qun
Liang, Kung-Hao
author_facet Yang, De-Ming
Chang, Tai-Jay
Hung, Kai-Feng
Wang, Mong-Lien
Cheng, Yen-Fu
Chiang, Su-Hua
Chen, Mei-Fang
Liao, Yi-Ting
Lai, Wei-Qun
Liang, Kung-Hao
author_sort Yang, De-Ming
collection PubMed
description COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart healthcare solutions that address major requirements for coping with the COVID-19 pandemic, including (1) the continuous monitoring of severe acute respiratory syndrome coronavirus 2, (2) patient stratification with distinct short-term outcomes (eg, mild or severe diseases) and long-term outcomes (eg, long COVID), and (3) adherence to medication and treatments for patients with COVID-19. Smart healthcare often utilizes medical artificial intelligence (AI) and cloud computing and integrates cutting-edge biological and optoelectronic techniques. These are valuable technologies for addressing the unmet needs in the management of COVID. By leveraging deep learning/machine learning capabilities and big data, medical AI can perform precise prognosis predictions and provide reliable suggestions for physicians’ decision-making. Through the assistance of the Internet of Medical Things, which encompasses wearable devices, smartphone apps, internet-based drug delivery systems, and telemedicine technologies, the status of mild cases can be continuously monitored and medications provided at home without the need for hospital care. In cases that develop into severe cases, emergency feedback can be provided through the hospital for rapid treatment. Smart healthcare can possibly prevent the development of severe COVID-19 cases and therefore lower the burden on intensive care units.
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spelling pubmed-98476852023-01-19 Smart healthcare: A prospective future medical approach for COVID-19 Yang, De-Ming Chang, Tai-Jay Hung, Kai-Feng Wang, Mong-Lien Cheng, Yen-Fu Chiang, Su-Hua Chen, Mei-Fang Liao, Yi-Ting Lai, Wei-Qun Liang, Kung-Hao J Chin Med Assoc Review Articles COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart healthcare solutions that address major requirements for coping with the COVID-19 pandemic, including (1) the continuous monitoring of severe acute respiratory syndrome coronavirus 2, (2) patient stratification with distinct short-term outcomes (eg, mild or severe diseases) and long-term outcomes (eg, long COVID), and (3) adherence to medication and treatments for patients with COVID-19. Smart healthcare often utilizes medical artificial intelligence (AI) and cloud computing and integrates cutting-edge biological and optoelectronic techniques. These are valuable technologies for addressing the unmet needs in the management of COVID. By leveraging deep learning/machine learning capabilities and big data, medical AI can perform precise prognosis predictions and provide reliable suggestions for physicians’ decision-making. Through the assistance of the Internet of Medical Things, which encompasses wearable devices, smartphone apps, internet-based drug delivery systems, and telemedicine technologies, the status of mild cases can be continuously monitored and medications provided at home without the need for hospital care. In cases that develop into severe cases, emergency feedback can be provided through the hospital for rapid treatment. Smart healthcare can possibly prevent the development of severe COVID-19 cases and therefore lower the burden on intensive care units. Lippincott Williams & Wilkins 2022-10-13 2023-02 /pmc/articles/PMC9847685/ /pubmed/36227021 http://dx.doi.org/10.1097/JCMA.0000000000000824 Text en Copyright © 2022, the Chinese Medical Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.
spellingShingle Review Articles
Yang, De-Ming
Chang, Tai-Jay
Hung, Kai-Feng
Wang, Mong-Lien
Cheng, Yen-Fu
Chiang, Su-Hua
Chen, Mei-Fang
Liao, Yi-Ting
Lai, Wei-Qun
Liang, Kung-Hao
Smart healthcare: A prospective future medical approach for COVID-19
title Smart healthcare: A prospective future medical approach for COVID-19
title_full Smart healthcare: A prospective future medical approach for COVID-19
title_fullStr Smart healthcare: A prospective future medical approach for COVID-19
title_full_unstemmed Smart healthcare: A prospective future medical approach for COVID-19
title_short Smart healthcare: A prospective future medical approach for COVID-19
title_sort smart healthcare: a prospective future medical approach for covid-19
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847685/
https://www.ncbi.nlm.nih.gov/pubmed/36227021
http://dx.doi.org/10.1097/JCMA.0000000000000824
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