Tutorial: Causal Inference in Biomedical Data Analytics - Basics and Recent Advances

Causal questions are being answered every day in the biomedical domain, and have significant impact on biomedical experimentation design, data analysis, and healthcare decision making. In this tutorial, we focus on identifying the (quantitative) causal effect of interventions. We will introduce a) introduction of causal inference, and popular frameworks for formulating causal inference; b) basics of causal effect identification algorithms; c) state-of-the-art methods by incorporating deep learning and machine learning; d) applications in biomedical data analytics, as well as challenges and opportunities moving forward.