Novel Alzheimer's disease subtypes identified using a data and knowledge driven strategy.

ABSTRACT: The population of adults with Alzheimer's disease (AD) varies in needs and outcomes. The heterogeneity of current AD diagnostic subgroups impedes the use of data analytics in clinical trial design and translation of findings into improved care. The purpose of this project was to define more clinically-homogeneous groups of AD patients and link clinical characteristics with biological markers. We used an innovative big data analysis strategy, the 3C strategy, that incorporates medical knowledge into the data analysis process. A large set of preprocessed AD Neuroimaging Initiative (ADNI) data was analyzed with 3C. The data analysis yielded 6 new disease subtypes, which differ from the assigned diagnosis types and present different patterns of clinical measures and potential biomarkers. Two o

SUBMITTER: Mitelpunkt A 

PROVIDER: S-EPMC6987140 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature