Digital Twin Technology in Healthcare: A Literature Review
2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE 2024): Proceedings
2024
Marta Narigina,
Andrejs Romānovs,
Rasa Bruzgiene
In our study, we review the literature from popular databases on how digital twins and machine learning can change healthcare and improve patient outcomes. The main research direction is the history of this area of investigation: the approaches to methodology; the recognition of trends in their reproduction; and the realization of empirics in practice. The paper also addresses the challenges as well as prospects in the field with a keen focus on digital twins' impact on healthcare innovation and service delivery. The purpose of the research is to evaluate the potential of digital twin technology to change the healthcare system by means of novel medical practices and improving patient care. It is expected that digital twin technology will usher in a new era in healthcare.
Keywords
Big data; Digital Twins; Empirical Research; Healthcare; Machine Learning; Predictive Healthcare
DOI
10.1109/AIEEE62837.2024.10586661
Hyperlink
https://ieeexplore.ieee.org/document/10586661
Narigina, M., Romānovs, A., Bruzgiene, R. Digital Twin Technology in Healthcare: A Literature Review. In: 2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE 2024): Proceedings, Latvia, Valmiera, 31 May-1 Jun., 2024. Piscataway: IEEE, 2024, pp.1-8. ISBN 979-8-3315-2777-8. e-ISBN 979-8-3315-2776-1. ISSN 2689-7334. e-ISSN 2689-7342. Available from: doi:10.1109/AIEEE62837.2024.10586661
Publication language
English (en)