yutong mao

Abstract Alzheimer’s disease (AD) is a complex, multifactorial neurodegenerative disorder with substantial heterogeneity in progression and treatment response. Despite recent therapeutic advances, predictive models capable of accurately forecasting individualized future biomarker states remain limited. Here, we present a machine learning-based operator learning framework for personalized modeling of AD progression, integrating longitudinal multimodal imaging, biomarker, and clinical data.

This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Jianxu Zhou *, Chaoqun Li and Yutong Mao College of Water Conservancy and Hydropower Engineering, Hohai University, 1 Xikang Road, Nanjing 210098, China * Author to whom correspondence should be addressed.