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Title

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort

Authors
Stamate, Daniel
Kim, Min
Proitsi, Petroula
Westwood, Sarah
Baird, Alison
Nevado-Holgado, Alejo
Hye, Abdul
Bos, Isabelle
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Published in Alzheimer's & dementia. 2019, vol. 5, p. 933-938
Abstract Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers.
Keywords Alzheimer's diseaseBiomarkersEMIF-ADMachine-LearningMetabolomics
Identifiers
PMID: 31890857
Full text
Structures
Research group Troubles de mémoire et maladie d'Alzeimer (935)
Project
European Commission: EMIF
Citation
(ISO format)
STAMATE, Daniel et al. A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort. In: Alzheimer's & dementia, 2019, vol. 5, p. 933-938. doi: 10.1016/j.trci.2019.11.001 https://archive-ouverte.unige.ch/unige:140840

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Deposited on : 2020-09-06

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