Discover the results of the largest, real-world, federated learning study focusing on glioblastoma and leveraging data from thousands of patients across six continents. The speaker, Dr. Bakas, comes from the University of Pennsylvania’s Perelman School of Medicine.

Attend the March Imaging and Informatics Community Webinar to hear about the application of artificial intelligence in healthcare.

Learn more about open-source artificial intelligence and machine learning models available to you!

Learn more about the safety and ethics of artificial intelligence in healthcare.

In the second part of this two-part webinar series, join NIH’s Office of Science Policy and Office of Extramural Research to learn more about the 2023 NIH DMS Policy, including privacy protections for data and justifiable limitations on sharing data.

Learn from NIH science policy and extramural research experts about the 2023 DMS policy and how it’s anticipated to affect the preservation and sharing of scientific data generated from NIH-funded or conducted research.

The NCI Center for Cancer Research’s Dr. Eytan Ruppin will present on “SELECT,” a computational approach that aims to identify clinically relevant synthetic lethal interactions and then harnesses them to predict patient response to cancer therapy from the bulk tumor transcriptome.

Dr. Obi L. Griffith will discuss CIViC, an open access, open source, community-driven web resource for clinical interpretation of variants in cancer. The goal of this resource is to enable precision medicine by providing an educational forum for dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations.

Dr. Svitlana Volkova will discuss a suite of augmented intelligence solutions powered by Artificial Intelligence models. She’ll show how these models can be used to detect, anticipate, and reason with technical expertise and capability development to analyze and extract knowledge from large amounts of unstructured scientific literature data.

Dr. Grassberger will highlight the current computational and mathematical approaches for modeling the impact of radiotherapy on the immune system, as well as designing the next generation of combination trials.