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    Patient-level effectiveness prediction modeling for glioblastoma using classification trees

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    Publication type
    Journal article with impact factor
    Author
    Geldof, Tine
    Van Damme, Nancy
    Huys, Isabelle
    Van Dyck, Walter
    Publication Year
    2020
    Journal
    Frontiers in Pharmacology
    Publication Volume
    10
    Publication Issue
    January
    Publication Begin page
    1
    Publication End page
    10
    
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    Abstract
    Little research has been done in pharmacoepidemiology on the use of machine learning for exploring medicinal treatment effectiveness in oncology. Therefore, the aim of this study was to explore the added value of machine learning methods to investigate individual treatment responses for glioblastoma patients treated with temozolomide.
    Keyword
    Real-world Evidence (RWE), Oncology, Exploratory Study, Propensity Score Modeling, Decision Tree, Machine Learning
    Knowledge Domain/Industry
    Special Industries : Healthcare Management
    DOI
    10.3389/fphar.2019.01665
    URI
    http://hdl.handle.net/20.500.12127/6426
    ae974a485f413a2113503eed53cd6c53
    10.3389/fphar.2019.01665
    Scopus Count
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