Toward Clinical Digital Twins: A ThreeDimensional Framework for Knowledge Extraction, Pathway Modeling, and Visualization Using MIMIC-IV Data...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.

This paper explores three dimensions of digital twin development in healthcare: knowledge extraction, clinical pathway modeling, and conceptual visualization. Using the Medical Information Mart for Intensive Care IV (MIMICIV) database, the study investigates how unsupervised learning, event-log anal...

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Publicado en:Studies in Health Technology & Informatics Vol. 336; pp. 1639 - 1644
Autores principales: BABIC, Ankica, RØISE, William, Kraft SAHLGAARD, Carl Oskar, SÆVAREID, Ida Wergeland
Formato: proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2026
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      pub: Sage Publications Inc.
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        atl: Toward Clinical Digital Twins: A ThreeDimensional Framework for Knowledge Extraction, Pathway Modeling, and Visualization Using MIMIC-IV Data...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.
      aug:
        au:
          BABIC, Ankica
          RØISE, William
          Kraft SAHLGAARD, Carl Oskar
          SÆVAREID, Ida Wergeland
        affil: Department of Information Science and Media Studies, University of Bergen, Norway.
      sug:
        subj:
          Digital Technology
          Critical Path
          Knowledge Management
          Data Mining
          Models, Theoretical
          Congresses and Conferences Italy
          Italy
          Human
          Adult
          Data Analytics
          Intensive Care Units
          Arthroplasty
          Decision Support Systems, Clinical
          User-Computer Interface
          Cluster Analysis
          Machine Learning
          Patient Centered Care
          Adult: 19-44 years
      ab: This paper explores three dimensions of digital twin development in healthcare: knowledge extraction, clinical pathway modeling, and conceptual visualization. Using the Medical Information Mart for Intensive Care IV (MIMICIV) database, the study investigates how unsupervised learning, event-log analysis, and visualization design can be combined to support the instantiation of clinical digital twins. The proposed framework integrates patient similarity modeling, temporal pathway reconstruction, and user-oriented visualization into a coherent design science research artifact. Although the resulting implementation does not yet constitute a fully realized clinical digital twin, it illustrates how digital twins can be initialized from real-world clinical data, support early predictive modeling, and evolve through iterative refinement. The findings highlight the importance of data granularity, temporal structure, and interpretability, and demonstrate how such models may bridge analytical and clinical perspectives. Future work will extend the framework through richer data inclusion, clinical validation, and real-time deployment.
      pubtype: Academic Journal
      doctype:
        proceedings
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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