ArticleProceedings. IEEE International Conference on Healthcare Informatics2026
Quantifying the Uncertainty and Risk Contributions of Activities of Daily Living Features in Dementia Prediction.
Article in Proceedings. IEEE International Conference on Healthcare Informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Activities of daily living (ADL) features contain important prognostic signals for future dementia and improve prediction model performance. However, assessing their contributions to predictive performance alone is insufficient to demonstrate how consistently and reliably individual ADL features contribute to dementia progression. To develop trustworthy and clinically actionable predictions using ADL features, it is crucial to quantify the prediction uncertainty associated with these features. This study introduces an uncertainty-aware framework combining credibility scores to quantify the uncertainty of the prediction model. Then, we measure the SHapley Additive exPlanations-based contributions of five-year impairment in each ADL to the predicted risk and model uncertainty. To address age-specific ADL patterns, we analyzed the contributions across different age groups. Our finding demonstrates that ADL impairments driving
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