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IR-GPT: AI Foundation Models to Optimize Interventional Radiology
Jacqueline L Brenner1, James T Anibal2,3, Lindsey A Hazen1
1Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health (NIH), Bethesda, USA.
Abstract:
Foundation artificial intelligence (AI) models are capable of complex tasks that involve text, medical images, and many other types of data, but have not yet been customized for procedural medicine. This report reviews prior work in deep learning related to interventional radiology (IR), identifying barriers to generalization and deployment at scale. Moreover, this report outlines the potential design of an "IR-GPT" foundation model to provide a unified platform for AI in IR, including data collection, annotation, and training methods-while also contextualizing challenges and highlighting potential downstream applications.
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