What is it about?

The digital twin is a versatile, digital version of the physical entity. In healthcare, medical digital twin features patient twin, which can help doctors predict, personalize, and improve treatment. But there's a problem: most digital twins can share data, but barely able to seamlessly communicate its true meaning. Some of the contributing factors of include different formats, different systems, and different ways of describing the same medical information. This review looks at the known significant potential of digital twins in healthcare, which somehow limited by interoperability constraints, and what can be done about it. The authors identify three main barriers: a lack of common technical standards, incompatible data formats, and the challenge of making sure data means the same thing across different systems (for example, a blood pressure reading from a wearable device should mean the same as one from a hospital monitor). The paper also highlights solutions, such as creating open data platforms, using standardized protocols, and improving how data is understood across systems. The goal is to help digital twins work together — enabling real-time monitoring, early intervention, and truly personalized care.

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Why is it important?

Without interoperability, medical digital twins cannot work together — and their potential to transform healthcare remains out of reach.

Perspectives

Interoperability is not just a technical challenge — it is the foundation for connected, patient-centered care. Our team came from different fields: health informatics, digital health, clinical medicine, and biomedical engineering. We realized that no single discipline can solve interoperability alone. This review reflects that belief — a synthesis, not a silo. We hope it inspires active collaboration, towards dynamic patient care.

DR. TENGKU AHMAD ISKANDAR TENGKU ALANG
Cyberjaya University College of Medical Sciences

Read the Original

This page is a summary of: Medical Digital Twin Technology for Interoperability: Challenges and Opportunities, Biomedical Engineering and Computational Biology, March 2026, SAGE Publications,
DOI: 10.1177/11795972261431928.
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