Bayesian Networks for Causal Reasoning by Tavpritesh Sethi

Explore advanced concepts in Bayesian Networks for causal reasoning in this fourth lecture of the series. Delve into the application of Bayesian methods in healthcare and disease modeling as part of the "Machine Learning for Health and Disease" program. Learn how to leverage these powerful statistical tools to analyze complex medical data, predict patient outcomes, and infer causal relationships in clinical settings. Gain insights from expert Tavpritesh Sethi on integrating Bayesian Networks with machine learning techniques to address real-world health challenges. Suitable for PhD students in STEM fields, medical students, postdoctoral fellows, faculty, and professionals interested in applying advanced statistical methods to improve healthcare decision-making and research.