Expanding research on clinical agent data to a virtual space of location, time, and context: exploration of data structures and limitations using a pragmatic digital twin - Takeaways - MDSpire
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Advancing the Utilization of Clinical Agent Data in a Virtual Environment: An Investigation into Data Structures and Constraints through a Pragmatic Digital Twin Approach

  • By

  • Sidra Rashid

  • Katarina Sliepkova

  • Lukas Bernhard

  • Sonja Stabenow

  • Emily Spicker

  • Stefanie Rinderle-Ma

  • Johannes Fottner

  • Dirk Wilhelm

  • Maximilian Berlet

  • September 19, 2026

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  • 1

    The increasing availability of digital healthcare data has accelerated the adoption of AI for disease identification and predictive analytics.

  • 2

    Healthcare data are often heterogeneous and unstructured, leading to significant interoperability challenges among various Electronic Health Record systems.

  • 3

    Patient-data fragmentation hinders the integration of multi-modal datasets necessary for effective data mining and machine learning in healthcare.

  • 4

    OMNI-SYS is a pragmatic digital twin framework designed to model hospital agents as objects, facilitating real-time updates and context-rich data extraction.

  • 5

    A feasibility study at TUM University Hospital assessed the application of oHIS-like platforms in recording pre-operative patient tracks using volunteer participants.

Original Source(s)

Expanding research on clinical agent data to a virtual space of location, time, and context: exploration of data structures and limitations using a pragmatic digital twin

  • by Sidra Rashid, Katarina Sliepkova, Lukas Bernhard, Sonja Stabenow, Emily Spicker, Stefanie Rinderle-Ma, Johannes Fottner, Dirk Wilhelm, Maximilian Berlet

  • September 19, 2026

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