TY - JOUR
T1 - Digital Twins for Healthcare 4.0
T2 - Recent Advances, Architecture, and Open Challenges
AU - Alazab, Mamoun
AU - Khan, Latif U.
AU - Koppu, Srinivas
AU - Ramu, Swarna Priya
AU - M, Iyapparaja
AU - Boobalan, Parimala
AU - Baker, Thar
AU - Maddikunta, Praveen Kumar Reddy
AU - Gadekallu, Thippa Reddy
AU - Aljuhani, Ahamed
PY - 2023/11/1
Y1 - 2023/11/1
N2 - Recent trends have shown a widespread increase in the landscape of digital healthcare (i.e., Healthcare 4.0) services, such as personalized healthcare, intelligent rehabilitation, telemedicine, and smart diet management, among others. These healthcare services are based on a variety of diverse requirements. Fulfilling these requirements require proactive intelligent analytics and self-sustainability of networks. Self-sustainability enables the operation of a network with minimum possible interaction from the end-users/network operators, whereas proactive intelligent analytics enables efficient management of resources in response to users' requests. To enable healthcare 4.0 with proactive online analytics and self-sustainability, one can leverage digital twins. In this article, we present an overview and recent advances of digital twins for healthcare 4.0. An architecture of digital twins for healthcare is also proposed. Furthermore, we present several use cases of digital twins. Finally, we present open research challenges with possible solutions.
AB - Recent trends have shown a widespread increase in the landscape of digital healthcare (i.e., Healthcare 4.0) services, such as personalized healthcare, intelligent rehabilitation, telemedicine, and smart diet management, among others. These healthcare services are based on a variety of diverse requirements. Fulfilling these requirements require proactive intelligent analytics and self-sustainability of networks. Self-sustainability enables the operation of a network with minimum possible interaction from the end-users/network operators, whereas proactive intelligent analytics enables efficient management of resources in response to users' requests. To enable healthcare 4.0 with proactive online analytics and self-sustainability, one can leverage digital twins. In this article, we present an overview and recent advances of digital twins for healthcare 4.0. An architecture of digital twins for healthcare is also proposed. Furthermore, we present several use cases of digital twins. Finally, we present open research challenges with possible solutions.
KW - Consumer electronics
KW - Data models
KW - Digital twins
KW - Information technology
KW - Mathematical models
KW - Medical services
KW - Wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85139388970&partnerID=8YFLogxK
U2 - 10.1109/MCE.2022.3208986
DO - 10.1109/MCE.2022.3208986
M3 - Article
AN - SCOPUS:85139388970
SN - 2162-2248
VL - 12
SP - 29
EP - 37
JO - IEEE Consumer Electronics Magazine
JF - IEEE Consumer Electronics Magazine
IS - 6
ER -