Machine learning methods for propensity and disease risk score estimation in high-dimensional data: a plasmode simulation and real-world data cohort analysis

• मुख्य लेखकों: Yuchen Guo (लेखक), Victoria Y. Strauss (लेखक), Martí Català (लेखक), Annika M. Jödicke (लेखक), Sara Khalid (लेखक), Daniel Prieto-Alhambra (लेखक)
• स्वरूप: पुस्तक
• प्रकाशित: Frontiers Media S.A., 2024-10-01T00:00:00Z.
• विषय: article
• ऑनलाइन पहुंच: Connect to this object online.

IntroductionMachine learning (ML) methods are promising and scalable alternatives for propensity score (PS) estimation, but their comparative performance in disease risk score (DRS) estimation remains unexplored.MethodsWe used real-world data comparing antihypertensive users to non-users with 69 neg...