DeepPlaque: A scalable multimodal platform for Aβ pathology and cell analysis in Alzheimer's disease

ABSTRACT: Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characterized by beta-amyloid (Aβ) plaques that exist as diffuse, fibrillar, and core species, with distinct toxicity levels. However, accurate classification of Aβ plaque types in postmortem brain tissues and profiling of surrounding cells present significant challenges. To address these challenges, we developed "DeepPlaque," an integrated system featuring "PlaqueNet," a deep learning model for automated classification of Aβ plaque species from diverse imaging platforms. DeepPlaque includes automated workflows for cellular phenotyping and proteomic profiling through targeted laser microdissection. PlaqueNet achieves expert-level accuracy (AUC > 90%)

SUBMITTER: Nancy Ip 

PROVIDER: S-SCDT-10_1038-S44321-026-00488-4 | biostudies-other |

REPOSITORIES: biostudies-other