Design for a Digital Twin in Clinical Patient Care

[2505.01206] Design for a Digital Twin in Clinical Patient Care Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Software Engineering arXiv:2505.01206 (cs) [Submitted on 2 May 2025 ( v1 ), last revised 9 Apr 2026 (this version, v2)] Title: Design for a Digital Twin in Clinical Patient Care Authors: Anna-Katharina Nitschke (1), Carlos Brandl (1), Fabian Egersdörfer (1), Magdalena Görtz (2 and 3), Markus Hohenfellner (3), Matthias Weidemüller (1) ((1) Physikalisches Institut, Universität Heidelberg, Heidelberg, Germany, (2) Junior Clinical Cooperation Unit 'Multiparametric Methods for Early Detection of Prostate Cancer', German Cancer Research Center (DKFZ), Heidelberg, Germany, (3) Department of Urology, Heidelberg University Hospital, Heidelberg, Germany) View a PDF of the paper titled Design for a Digital Twin in Clinical Patient Care, by Anna-Katharina Nitschke (1) and 16 other authors View PDF HTML (experimental) Abstract: Digital Twins hold great potential to personalize clinical patient care, provided the concept is translated to meet specific requirements emerging from established clinical workflows. We present a general and unspecialized Digital Twin design combining knowledge graphs and ensemble learning to reflect the entire patient's clinical journey and assist clinicians in their decision-making. Such a design is predictive, modular, evolving, informed, interpretable and explainable, thus opening broad clinical applications. Comments: Accepted version of the journal. Added clinical examples in the supplementary material and revised the introduction and section 3 Subjects: Software Engineering (cs.SE) ; Computational Engineering, Finance, and Science (cs.CE); Medical Physics (physics.med-ph) Cite as: arXiv:2505.01206 [cs.SE] (or arXiv:2505.01206v2 [cs.SE] for this version) https://doi.org/10.48550/arXiv.2505.01206 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1038/s44401-025-00060-1 Focus to learn more DOI(s) linking to related resources Submission history From: Carlos Brandl [ view email ] [v1] Fri, 2 May 2025 11:50:42 UTC (361 KB) [v2] Thu, 9 Apr 2026 22:09:28 UTC (1,781 KB) Full-text links: Access Paper: View a PDF of the paper titled Design for a Digital Twin in Clinical Patient Care, by Anna-Katharina Nitschke (1) and 16 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.SE < prev | next > new | recent | 2025-05 Change to browse by: cs cs.CE physics physics.med-ph References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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