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
- Social Determinants of Health with Large/Moderate Language Models on EHR Data: AI in Immuno-oncologyJuly 30, 2024CCDI Federated Data: Enhancing Data DiscoverabilityAugust 13, 2024Leveraging High-Performance Computing Resources and Using QIIME 2 to Advance Your Microbiome ProjectsAugust 27, 2024 - August 29, 2024NCI Office of Data Sharing’s Annual Data Sharing Symposium: Driving Cancer Advances Through Impactful ResearchOctober 16, 2024The Cancer Research Data Commons 2024 Fall Symposium: Ten Years of Empowering Cancer ResearchersOctober 16, 2024 - October 17, 2024