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Medical Digital Twin Technology for Interoperability: Challenges and Opportunities.

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Title: Medical Digital Twin Technology for Interoperability: Challenges and Opportunities.
Authors: Tengku Alang, Tengku Ahmad Iskandar1 (AUTHOR) tengku.a.iskandar@cyberjaya.edu.my, Lee, Yeong Yeh2,3 (AUTHOR), Tan, Tian Swee4,5 (AUTHOR), Mokhtar, Ariffin Marzuki6 (AUTHOR)
Source: Biomedical Engineering & Computational Biology. 3/29/2026, Vol. 17, p1-8. 8p.
Subjects: Digital twin, Data harmonization, Data structures, Computer network protocols, Individualized medicine, Digital health
Abstract: Digital twins (DT) technology has shown considerable growth in recent years. Previous studies have examined technologies in a variety of areas, including health care. However, limited studies have attempted to provide a thorough discussion of strategies for the seamless integration of DT into health care, particularly in the context of interoperability of heterogeneous medical data. This review examines the underlying concept of DT and its possible integration in healthcare, particularly in the context of healthcare interoperability. It also analyzes the main problems such as the lack of standardized protocols, the non-homogeneity of data formats and technical complexity. Finally, potential opportunities are highlighted such as standardized protocol, the creation of an open data platform and the empowerment of semantic interoperability. In conclusion, this review has provided valuable insights for many professionals, including researchers and healthcare providers, which will contribute to empowering patient-centered or personalized medicine and to the development of digital health. [ABSTRACT FROM AUTHOR]
Copyright of Biomedical Engineering & Computational Biology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Biomedical+Engineering+%26+Computational+Biology%22">Biomedical Engineering & Computational Biology</searchLink>. 3/29/2026, Vol. 17, p1-8. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Data+harmonization%22">Data harmonization</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures%22">Data structures</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+protocols%22">Computer network protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Individualized+medicine%22">Individualized medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+health%22">Digital health</searchLink>
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  Data: Digital twins (DT) technology has shown considerable growth in recent years. Previous studies have examined technologies in a variety of areas, including health care. However, limited studies have attempted to provide a thorough discussion of strategies for the seamless integration of DT into health care, particularly in the context of interoperability of heterogeneous medical data. This review examines the underlying concept of DT and its possible integration in healthcare, particularly in the context of healthcare interoperability. It also analyzes the main problems such as the lack of standardized protocols, the non-homogeneity of data formats and technical complexity. Finally, potential opportunities are highlighted such as standardized protocol, the creation of an open data platform and the empowerment of semantic interoperability. In conclusion, this review has provided valuable insights for many professionals, including researchers and healthcare providers, which will contribute to empowering patient-centered or personalized medicine and to the development of digital health. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Biomedical Engineering & Computational Biology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/11795972261431928
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        Text: English
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        Type: general
      – SubjectFull: Data harmonization
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      – SubjectFull: Data structures
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      – SubjectFull: Computer network protocols
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      – SubjectFull: Individualized medicine
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              Text: 3/29/2026
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              Y: 2026
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