title: Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.
abstract: Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
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mesh_terms: D000544:Alzheimer Disease / Q000150:complications* / Q000235:genetics; D001057:Apolipoproteins E / Q000235:genetics; D015415:Biomarkers; D003072:Cognition Disorders / Q000175:diagnosis* / Q000209:etiology* / Q000235:genetics; D019295:Computational Biology; D016206:Databases, Bibliographic / Q000706:statistics & numerical data; D006801:Humans; D011237:Predictive Value of Tests
chemical_list: D001057:Apolipoproteins E; D015415:Biomarkers
keywords: Azheimer's disease; Big data; Bioinformatics; Biomarkers; Cognitive decline; Crowdsource; Genetics; Imaging