Video is available - Log in to view. You must be registered to the event to view content
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.
Armando Teixeira-Pinto, Australia
Understanding causal inferences in transplantation
Dr. Dorry Segev, United States
Machine learning to predict transplant outcomes: Helpful or hype?
right-click to download
