Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint DOI Creative Commons
Stanislas Demuth, de Sèze, Gilles Edan

и другие.

JMIR Medical Informatics, Год журнала: 2025, Номер 13, С. e53542 - e53542

Опубликована: Янв. 28, 2025

Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of medical "digital twin" has recently become popular to designate digital representations patients as support for wide range data science applications. However, the is ambiguous when it comes practical implementations. Here, we propose twin framework with data-centric approach. We argue that single representation cannot all uses twins technical and regulatory reasons. Instead, architecture leveraging three main families representations: (1) multimodal dashboards integrating various raw health records at points care assist perception documentation, (2) virtual patients, which provide nonsensitive collective secondary uses, (3) individual predictions For given patient, multiple may be generated according different pathways patient goes through, each tailored balance trade-offs associated respective intended uses. Therefore, our proposed conceives several along pathways.

Язык: Английский

Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint DOI Creative Commons
Stanislas Demuth, de Sèze, Gilles Edan

и другие.

JMIR Medical Informatics, Год журнала: 2025, Номер 13, С. e53542 - e53542

Опубликована: Янв. 28, 2025

Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of medical "digital twin" has recently become popular to designate digital representations patients as support for wide range data science applications. However, the is ambiguous when it comes practical implementations. Here, we propose twin framework with data-centric approach. We argue that single representation cannot all uses twins technical and regulatory reasons. Instead, architecture leveraging three main families representations: (1) multimodal dashboards integrating various raw health records at points care assist perception documentation, (2) virtual patients, which provide nonsensitive collective secondary uses, (3) individual predictions For given patient, multiple may be generated according different pathways patient goes through, each tailored balance trade-offs associated respective intended uses. Therefore, our proposed conceives several along pathways.

Язык: Английский

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