NeuroFANN: identification of neuropathological subtypes in dementia with plasma proteins by using functionally annotated neural network.

ABSTRACT: Dementia diagnosis relies on identifying neuropathological features, such as beta-amyloid (Aβ) deposition, medial temporal lobe atrophy (MTA), and white matter hyperintensity (WMH). Recently, plasma protein biomarkers have emerged as a cost-effective and less invasive tool for identifying neuropathological features, enhanced by machine learning (ML) for precise diagnosis. However, most ML studies fail to account for protein-protein interactions (PPIs) and synergetic effects between proteins, overlooking their collective contributions to disease mechanisms. Additionally, the lack of consideration for functional properties may result in the redundant and imbalanced representation of proteins and their functions, potentially limiting the effectiveness of dementia diagnosis. In this study, we

SUBMITTER: Park S 

PROVIDER: S-EPMC12315549 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature