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
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29th Annual Meeting and Education Day of the Society for Neuro-Oncology (SNO)November 21, 2024 - November 24, 2024Leveraging Optical Imaging and Data Science to Enable Precision Intervention in Brain Tumor SurgeryNovember 26, 2024Evaluating AI Models: Benchmarking and FairnessNovember 26, 20242024 U.S. Southeast Healthcare Innovation SummitDecember 04, 2024