Patient-level effectiveness prediction modeling for glioblastoma using classification trees
Publication typeJournal article with impact factor
JournalFrontiers in Pharmacology
Publication Begin page1
Publication End page10
MetadataShow full item record
AbstractLittle 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.
KeywordReal-world Evidence (RWE), Oncology, Exploratory Study, Propensity Score Modeling, Decision Tree, Machine Learning
Knowledge Domain/IndustrySpecial Industries : Healthcare Management
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