A transition-based digital twin model for Alzheimer's disease predicts cognitive status and diagnosis from sparse longitudinal data more accurately than sequence-based alternatives while quantifying uncertainty.
arXiv preprint arXiv:2002.03419 (2020)
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Transition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data
A transition-based digital twin model for Alzheimer's disease predicts cognitive status and diagnosis from sparse longitudinal data more accurately than sequence-based alternatives while quantifying uncertainty.