Toward a generalizable machine learning workflow for neurodegenerative disease staging with focus on neurofibrillary tangles.

ABSTRACT: Machine learning (ML) has increasingly been used to assist and expand current practices in neuropathology. However, generating large imaging datasets with quality labels is challenging in fields which demand high levels of expertise. Further complicating matters is the often seen disagreement between experts in neuropathology-related tasks, both at the case level and at a more granular level. Neurofibrillary tangles (NFTs) are a hallmark pathological feature of Alzheimer disease, and are associated with disease progression which warrants further investigation and granular quantification at a scale not currently accessible in routine human assessment. In this work, we first provide a baseline of annotator/rater agreement for the tasks of Braak NFT staging between experts and NFT detection u

SUBMITTER: Vizcarra JC 

PROVIDER: S-EPMC10726581 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature