Digital Twins in Neurology Care: Evidence, Limitations, and a Path Forward - PubMed
3 hours ago
- #neurology
- #clinical decision support
- #digital twins
- Digital twins in neurology are defined as dynamically updated, bidirectionally linked models that offer predictive, decision-relevant value, but current applications often lack this rigor.
- Existing systems in neurology (e.g., for dementia, multiple sclerosis, Parkinson's) are more accurately described as twin-inspired models for decision support or trial analytics, not true clinical digital twins.
- Neurology's suitability for digital twins stems from disease heterogeneity, multimodal data, and iterative care, but progress is hampered by issues in measurement validity, uncertainty handling, evaluation, and governance.
- A path forward emphasizes developing question-specific, validated digital twins over generalized brain twin narratives, framing current work as twin-inspired modeling rather than full digital twin implementation.