The Current State of Transparency for AI Models and Datasets
Join Dr. Aaron Lee from the University of Washington for a presentation on the importance of transparency in data sets used for training artificial intelligence (AI) models and their metadata.
Dr. Lee will:
- discuss the current landscape of artifacts that can enhance AI model transparency,
- provide metadata for data sets, and
- address recent efforts to adopt these tools in the NIH Bridge to Artificial Intelligence (Bridge2AI) program.
The NIH Common Fund’s Bridge2AI program addresses biomedical challenges that are beyond human intuition. The program utilizes both biomedical and behavioral research to develop AI and machine learning (ML) models.
To view upcoming speakers or recordings of past presentations, visit the CBIIT Data Science Seminar Series webpage.
The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.
Dr. Lee is an associate professor and vitreoretinal surgeon with the University of Washington’s Department of Ophthalmology.
Upcoming Events
- HLA-Arena: Enabling Structure-Guided Pipelines for Personalized Cancer Immunotherapy DesignApril 30, 2025AI-Driven Spatial Transcriptomics Unlocks Large-Scale Breast Cancer Biomarker Discovery from HistopathologyMay 07, 2025Co-clinical Imaging Research Resource Program (CIRP) Annual Virtual Meeting 2025—Celebrating A Ten-Year MilestoneMay 07, 2025 - May 08, 2025Agentic AI in Cancer ResearchMay 27, 2025BTEC 2025 Annual Conference: The Epidemiology of Brain Metastases for Adult and Pediatric Brain TumorsMay 29, 2025Ctrl+Alt+Cure: Driving Smarter Cancer CareJune 11, 2025