Research graph
References from Translational barriers to digital twins in radiation oncology. Local targets link to admitted publications; unresolved targets remain external evidence.
Digital twins for predictive oncology will be a paradigm shift for precision cancer care
10.1038/s41591-021-01558-5 · 2021 · External reference
Digital twins for health: a scoping review
10.1038/s41746-024-01073-0 · 2024 · External reference
Digital twins in medicine
10.1038/s43588-024-00607-6 · 2024 · External reference
Quo vadis Radiomics? Bibliometric analysis of 10-year Radiomics journey
10.1007/s00330-023-09645-6 · 2023 · External reference
10.1063/5.0086789
10.1063/5.0086789 · External reference
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What is a digital twin anyway? Deriving the definition for the built environment from over 15,000 scientific publications
10.1016/j.buildenv.2025.112748 · 2025 · External reference
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2024 · External reference
Application of digital twins for personalized oncology
10.1038/s41568-025-00850-7 · 2025 · External reference
10.3390/cancers16223817
10.3390/cancers16223817 · External reference
10.1136/bmj.n71
10.1136/bmj.n71 · External reference
Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems
2017 · External reference
A probabilistic graphical model foundation for enabling predictive digital twins at scale
10.1038/s43588-021-00069-0 · 2021 · External reference
Building digital twins of the human immune system: toward a roadmap
10.1038/s41746-022-00610-z · 2022 · External reference
The ‘digital twin’ to enable the vision of precision cardiology
10.1093/eurheartj/ehaa159 · 2020 · External reference
10.1088/1361-6560/ada684
10.1088/1361-6560/ada684 · External reference
10.1088/1361-6560/add9de
10.1088/1361-6560/add9de · External reference
Optimal treatment selection in sequential systemic and Locoregional therapy of oropharyngeal squamous carcinomas: deep Q-learning with a patient-physician digital twin dyad
10.2196/29455 · 2022 · External reference
DITTO: a visual digital twin for interventions and temporal treatment outcomes in head and neck Cancer
10.1109/tvcg.2024.3456160 · 2025 · External reference
10.3389/frai.2023.1222612
10.3389/frai.2023.1222612 · External reference
10.1186/s12911-026-03520-2
10.1186/s12911-026-03520-2 · External reference
In silico clinical trials: concepts and early adoptions
10.1093/bib/bby043 · 2019 · External reference
Prediction models need appropriate internal, internal–external, and external validation
10.1016/j.jclinepi.2015.04.005 · 2016 · External reference
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2019 · External reference
Assessing the generalizability of prognostic information
10.7326/0003-4819-130-6-199903160-00016 · 1999 · External reference
10.1136/bmj.m441
10.1136/bmj.m441 · External reference
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024 · External reference
PROBAST: a tool to assess risk of Bias and applicability of prediction model studies: explanation and elaboration
10.7326/m18-1377 · 2019 · External reference
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
10.1136/bmj-2022-070904 · 2022 · External reference
Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers
10.1148/ryai.2020200029 · 2020 · External reference
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