NCI Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence
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.
The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.
Dr. Fedorov is part of the Surgical Planning Laboratory at Brigham and Women's Hospital. He is also an associate professor at Harvard Medical School.
Upcoming Events
- Predicting Patients’ Response to Immunotherapy from Tumor Histopathology and Blood: Computational Science in Immuno-oncologyJuly 08, 2025Assessing the Tumor Microenvironment with Systems Immunology: Computational Science in Immuno-oncologyAugust 21, 2025Data Jamboree: Enhancing Childhood Cancer Data Sharing and UtilitySeptember 29, 2025 - September 30, 2025NCI Office of Data Sharing’s Annual Data Sharing Symposium 2025: How Data Advances the Impact of Cancer ResearchSeptember 30, 2025 - October 01, 2025Childhood Cancer Data Initiative (CCDI) Symposium 2025October 06, 2025 - October 07, 2025