318 Discovering Subgroups with Supervised Machine Learning Models for Heterogeneity of Treatment Effect Analysis
OBJECTIVES/GOALS: The goal of the study is to provide insights into the use of machine learning methods as a means to predict heterogeneity of treatment effect (HTE) in participants of randomized clinical trials. METHODS/STUDY POPULATION: Using data from 2,441 participants enrolled in the ASPirin in...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2024-04-01
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| Series: | Journal of Clinical and Translational Science |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2059866124002887/type/journal_article |