bibtext: @InProceedings{ Wan_Adaptive_MICCAI2024,
                   author = { Wang, Xinkai and Shi, Yonggang },
                   title = { { Adaptive Subtype and Stage Inference for Alzheimer’s Disease } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15003 },
                   month = {October},
                   pages = { pending },
                }
abstract: Subtype and Stage Inference (SuStaIn) is a useful Event-based Model for capturing both the temporal and the phenotypical patterns for any progressive disorders, which is essential for understanding the heterogeneous nature of such diseases. However, this model cannot capture subtypes with different progression rates with respect to predefined biomarkers with fixed events prior to inference. Therefore, we propose an adaptive algorithm for learning subtype-specific events while making subtype and stage inference. We use simulation to demonstrate the improvement with respect to various performance metrics. Finally, we provide snapshots of different levels of biomarker abnormality within different subtypes on Alzheimer’s Disease (AD) data to demonstrate the effectiveness of our algorithm.
title: Adaptive Subtype and Stage Inference for Alzheimer’s Disease
authors: Wang, Xinkai Shi, Yonggang