Virtual workshop “Leveraging Observational Data With Machine Learning”

The objective of this workshop is to:

• bring together main actors working with observational or real-world data, and developing biostatistics and machine learning models for causal inference
• present the state of the art in dynamic treatment regime (DRT)
• highlight the complementarity of using both Structural Causal Model and Potential Outcome point of views
• present the possibilities offered by real word data and by the integration of real word data and RCTs
  • Validate observational studies
  • Generalize the treatment effect in a target patient population
  • Better estimate the (heterogeneous) effects
  • Handle unobserved confounders
  • Help better designing RCT with better external validity
• discuss about which real word data should be collected
• promote collaboration between the different actors

This is an online event

More information can be found here.