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Concordance Plausibility Check for Intervention-Conditioned Human Digital Twins
Saeed Farzi, Christopher Kipps, John McBeth +7
Intervention-conditioned human digital twins predict treatment alternatives that cannot be observed in the same patient. Ordinary predictive accuracy therefore cannot establish cou…
Transition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data
Yinyu Huang, Yilin Zhang, Sofia Michopoulou +2
Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challenges for prediction and personal…
From Baseline to Follow-Up: Counterfactual Spine DXA Image Synthesis in UK Biobank Using a Causal Hierarchical Variational Autoencoder
Yilin Zhang, Nicholas C. Harvey, Nicholas R. Fuggle +1
Dual-energy X-ray absorptiometry (DXA) is widely used for large-scale skeletal assessment, yet learning controllable and interpretable factor-specific anatomical variation remains…
Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning
Alberto Tamajo, Srinandan Dasmahapatra, Rahman Attar
Neural networks suffer from catastrophic forgetting in class-incremental learning (CIL) settings. Rehearsal$\unicode{x2013}$replaying a subset of past samples$\unicode{x2013}$is a…