Description

This workshop aims to provide participants the fundamental principles of using machine learning techniques in transplantation. These include supervised, unsupervised, and reinforcement learning, real-world applications of machine learning, and knowledge of causal inference in machine learning. Examples of multi-omics integration and prediction models will also be presented. Clinical and non-technical attendees will enjoy the overview of this exciting field and the applied perspectives from the lectures. In addition, we will have a few technical “teaching assistants” available for those who have experience with R/Python and wish to bring their laptops and (simple) datasets to explore coding the examples.