Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine
Decision Systems (United States) · Massachusetts Institute of Technology · +4 more institutions
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Abstract
Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins in ensuring safety and efficacy, with examples in cardiology and oncology. We highlight challenges and opportunities for developing personalized trial methodologies, validation metrics, and standardizing VVUQ processes. VVUQ frameworks are essential for integrating digital twins into clinical practice.
Citation impact
61
total citations
- FWCI
- 30.25
- Percentile
- 100%
- References
- 111
Citations per year
Authors
9Topics & keywords
Topics
Keywords
- Precision medicine
- Perspective (graphical)
- Psychological intervention
- Computer science
- Data science
- Medical physics
- Model validation
- Digital health
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