NCI Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence
Data Science Seminar Series
February 21, 2024 | 11:00 AM – 12:00 PM
Virtual
Artificial intelligence (AI) is advancing. It’s changing the established approaches for how we acquire, study, and understand biomedical imaging data. Scientists (like you) need to continuously develop and refine AI technologies, and this requires easy access to high-quality, diverse, annotated data.
The NCI Cancer Research Data Commons’ Imaging Data Commons (IDC) hosts such data. In this seminar, Dr. Andrey Fedorov from Brigham and Women’s Hospital will address how IDC aims to:
- help refine AI tools by facilitating their development, validation, and clinical translation; and
- create reproducible and transparent AI processing pipelines.
About the Speaker
Andrey Fedorov, Ph.D.
Dr. Fedorov is part of the Surgical Planning Laboratory, in the Department of Radiology, Brigham and Women's Hospital and Harvard Medical. His research focuses on the translation and validation of medical image computing technology for clinical research applications, with an emphasis on quantitative imaging, imaging informatics, and image-guided interventional procedures.
About the Data Science Seminar Series
CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI's Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:
- How can AI be used for diagnosis, treatment, or omics research?
- What are the related laws and ethical considerations for AI?
- How can we empower an AI-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.