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    Stratification of amyotrophic lateral sclerosis patients: A crowdsourcing approach

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    Author
    Kueffner, R.
    Zach, N.
    Bronfeld, M.
    Date
    2019
    Journal
    Scientific Reports
    Publisher
    Nature Publishing Group
    Type
    Article
    
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    Show full item record
    See at
    https://doi.org/10.1038/s41598-018-36873-4
    Abstract
    Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease where substantial heterogeneity in clinical presentation urgently requires a better stratification of patients for the development of drug trials and clinical care. In this study we explored stratification through a crowdsourcing approach, the DREAM Prize4Life ALS Stratification Challenge. Using data from >10,000 patients from ALS clinical trials and 1479 patients from community-based patient registers, more than 30 teams developed new approaches for machine learning and clustering, outperforming the best current predictions of disease outcome. We propose a new method to integrate and analyze patient clusters across methods, showing a clear pattern of consistent and clinically relevant sub-groups of patients that also enabled the reliable classification of new patients. Our analyses reveal novel insights in ALS and describe for the first time the potential of a crowdsourcing to uncover hidden patient sub-populations, and to accelerate disease understanding and therapeutic development. Copyright The Author(s) 2019.
    Keyword
    DREAM Prize4Life ALS Stratification Challenge
    stratification of patients
    Amyotrophic Laterial Sclerosis
    Crowdsourcing--methods
    Identifier to cite or link to this item
    https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060520844&doi=10.1038%2fs41598-018-36873-4&partnerID=40&md5=cee2822d9e7d404d4b5ec2728f2e6fcd; http://hdl.handle.net/10713/10764
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41598-018-36873-4
    Scopus Count
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    UMB Open Access Articles 2019

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