Federated Learning for the Healthcare Metaverse: Concepts, Applications, Challenges, and Future Directions

被引:42
作者
Bashir, Ali Kashif [1 ,2 ,3 ]
Victor, Nancy [4 ]
Bhattacharya, Sweta [4 ]
Huynh-The, Thien [5 ]
Chengoden, Rajeswari [4 ]
Yenduri, Gokul [4 ]
Maddikunta, Praveen Kumar Reddy [4 ]
Pham, Quoc-Viet [6 ]
Gadekallu, Thippa Reddy [4 ,7 ,8 ,9 ,10 ]
Liyanage, Madhusanka [11 ]
机构
[1] Manchester Metropolitan Univ, Dept Comp & Math, Manchester M15 6BH, England
[2] Woxsen Univ, Woxsen Sch Business, Hyderabad 502345, India
[3] Lebanese Amer Univ, Dept Comp Sci & Math, Beirut 11022801, Lebanon
[4] Vellore Inst Technol, Sch Informat Technol, Vellore 632014, India
[5] Ho Chi Minh City Univ Technol & Educ, Dept Comp & Commun Engn, Ho Chi Minh City 71307, Vietnam
[6] Univ Dublin, Trinity Coll Dublin, Sch Comp Sci & Stat, Dublin 2, Ireland
[7] Lebanese Amer Univ Byblos, Dept Elect & Comp Engn, Byblos, Lebanon
[8] Zhongda Grp, Res & Dev Dept, Jiaxing 314312, Zhejiang, Peoples R China
[9] Jiaxing Univ, Coll Informat Sci & Engn, Jiaxing 314001, Peoples R China
[10] Lovely Profess Univ, Div Res & Dev, Phagwara 144001, India
[11] Univ Coll Dublin, Sch Comp Sci, Dublin 4, Ireland
关键词
Medical services; Metaverse; Data privacy; Medical diagnostic imaging; Artificial intelligence; Collaboration; Security; Cobots; digital twins; disease diagnosis; federated learning (FL); healthcare; healthcare metaverse; metaverse; PRIVACY PRESERVATION; MANAGEMENT; SYSTEMS;
D O I
10.1109/JIOT.2023.3304790
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent technological advancements have considerably improved healthcare systems to provide various intelligent services, improving life quality. The Metaverse, often described as the next evolution of the Internet, helps the users interact with each other and the environment, thus offering a seamless connection between the virtual and physical worlds. Additionally, the Metaverse, by integrating emerging technologies, such as artificial intelligence (AI), cloud edge computing, Internet of Things (IoT), blockchain, and semantic communications, can potentially transform many vertical domains in general and the healthcare sector (healthcare Metaverse) in particular. The healthcare Metaverse holds huge potential to revolutionize the development of intelligent healthcare systems, thus presenting new opportunities for significant advancements in healthcare delivery, personalized healthcare experiences, medical education, collaborative research, and so on. However, various challenges are associated with the realization of the healthcare Metaverse, such as privacy, interoperability, data management, and security. Federated learning (FL), a new branch of AI, opens up enormous opportunities to deal with the aforementioned challenges in the healthcare Metaverse by exploiting the data and computing resources available at the distributed devices. This motivated us to present a survey on adopting FL for the healthcare Metaverse. Initially, we present the preliminaries of IoT-based healthcare systems, FL in conventional healthcare, and the healthcare Metaverse. Furthermore, the benefits of the FL in the healthcare Metaverse are discussed. Subsequently, we discuss the several applications of FL-enabled healthcare Metaverse, including medical diagnosis, patient monitoring, medical education, infectious disease, and drug discovery. Finally, we highlight the significant challenges and potential solutions toward realizing FL in the healthcare Metaverse.
引用
收藏
页码:21873 / 21891
页数:19
相关论文
共 50 条
[21]   Metaverse for service industries: Future applications, opportunities, challenges and research directions [J].
Jung, Timothy ;
Cho, Justin ;
Han, Dai-In Danny ;
Ahn, Sun Joo ;
Gupta, Mansi ;
Das, Gopal ;
Heo, Cindy Yoonjoung ;
Loureiro, Sandra Maria Correia ;
Sigala, Marianna ;
Trunfio, Mariapina ;
Taylor, Alexandra ;
Dieck, M. Claudia tom .
COMPUTERS IN HUMAN BEHAVIOR, 2024, 151
[22]   Communication optimization techniques in Personalized Federated Learning: Applications, challenges and future directions [J].
Sabah, Fahad ;
Chen, Yuwen ;
Yang, Zhen ;
Raheem, Abdul ;
Azam, Muhammad ;
Ahmad, Nadeem ;
Sarwar, Raheem .
INFORMATION FUSION, 2025, 117
[23]   Metaverse applications in healthcare: opportunities and challenges [J].
Jeong, Euibeom ;
Lee, Donhee .
SERVICE BUSINESS, 2025, 19 (01)
[24]   Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions [J].
Hafi, Houda ;
Brik, Bouziane ;
Frangoudis, Pantelis A. ;
Ksentini, Adlen ;
Bagaa, Miloud .
IEEE ACCESS, 2024, 12 :9890-9930
[25]   Green and Economical Interaction in Metaverse: Challenges, Architecture, and Future Directions [J].
Zhao, Yaru ;
Huang, Yakun ;
Lu, Ping ;
Shi, Wenzhe ;
Ma, Baojun ;
Su, Xiang ;
Qiao, Xiuquan .
IEEE NETWORK, 2024, 38 (06) :300-308
[26]   Challenges and future directions of secure federated learning: a survey [J].
Kaiyue Zhang ;
Xuan Song ;
Chenhan Zhang ;
Shui Yu .
Frontiers of Computer Science, 2022, 16
[27]   Challenges and future directions of secure federated learning:a survey [J].
Kaiyue ZHANG ;
Xuan SONG ;
Chenhan ZHANG ;
Shui YU .
Frontiers of Computer Science, 2022, 16 (05) :169-176
[28]   Challenges and future directions of secure federated learning: a survey [J].
Zhang, Kaiyue ;
Song, Xuan ;
Zhang, Chenhan ;
Yu, Shui .
FRONTIERS OF COMPUTER SCIENCE, 2022, 16 (05)
[29]   Federated Learning for IoT: Applications, Trends, Taxonomy, Challenges, Current Solutions, and Future Directions [J].
Adam, Mumin ;
Baroudi, Uthman .
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2024, 5 :7842-7877
[30]   Exploring the convergence of Metaverse, Blockchain, and AI: A comprehensive survey of enabling technologies, applications, challenges, and future directions [J].
Uddin, Mueen ;
Obaidat, Muath ;
Manickam, Selvakumar ;
Laghari, Shams Ul Arfeen ;
Dandoush, Abdulhalim ;
Ullah, Hidayat ;
Ullah, Syed Sajid .
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2024, 14 (06)