Targeted Learning: From Machine Learning to Inference | Mark van der Laan, PhD | Sep 23, 2020

Minimizing confounding is a key challenge to ensuring the fidelity of observational assessments of the real-world safety and effectiveness of medical products. Significant advances have been made in leveraging data-driven machine learning approaches to efficiently reduce potential confounding. This webinar will focus on super learning and targeted maximum likelihood estimation, in particular, as solutions to reducing bias in observational studies of electronic health record data.

Видео Targeted Learning: From Machine Learning to Inference | Mark van der Laan, PhD | Sep 23, 2020 канала Sentinel Initiative