Introducing Imaging Data Commons Agentic Interfaces
Finding cancer imaging data sets shouldn't require advanced technical skills. In this Data Science Seminar Series session, Dr. Andrey Fedorov introduces two new tools (enabled by Large Language Models [LLMs]) that make it easier to search, explore, and work with 100+ terabytes of data in NCI’s Imaging Data Commons (IDC).
During the session Dr. Fedorov will demonstrate the latest IDC Model Context Protocol (MCP) server and the agent skill that can integrate with LLM-enabled assistants. He will show you how to:
- set up the IDC MCP server and agent skill to connect your assistant to IDC data
- find and access DICOM imaging data sets, or cohorts, by describing your research needs in everyday language
- use your assistant to brainstorm research questions, or hypotheses, for a specific data set
Whether you're a cancer researcher new to working with imaging data or a data scientist looking to simplify access to a large repository, this session shows you a more direct path to accessing data from the IDC.
Register today to save your spot and bring your questions for the live Q&A.
About the Speaker
Andrey Fedorov, Ph.D.
Dr. Fedorov is a researcher at Brigham and Women's Hospital (BWH) and associate professor in Radiology at Harvard Medical School. He is also one of the leads for the team building the NCI IDC. A computer scientist by training, Dr. Fedorov spent the past 15 years at the BWH Surgical Planning Lab working on translation and evaluation of image computing tools in clinical research applications. He is dedicated to developing infrastructure and best practices to help imaging researchers improve transparency of their studies, simplify data sharing and make their analyses more easily accessible and reproducible by others.
About NCI’s Cancer Research Data Commons
The IDC is one of seven data commons available through NCI’s Cancer Research Data Commons (CRDC), a secure, cloud-based, data science infrastructure that allows cancer researchers like you submit, share, access, and analyze data more effectively. IDC offers more than 100 terabytes of freely available multi-modal imaging from both clinical and basic cancer research studies.
About the Data Science Seminar Series
CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of Super Intelligence (SI) in cancer research and care. Brought to you by CBIIT and NCI’s Division of Cancer Treatment and Diagnosis SI working group, the upcoming webinars will explore a variety of questions, such as the following:
- How can SI be used for diagnosis, treatment, or omics research?
- What are the related laws and ethical considerations for SI?
- How can we empower an SI-ready cancer research community through workforce development, collaborations, and funding?
To view upcoming speakers or recordings of past presentations, visit the Data Science Seminar Series page.