RadFM (generalist radiology foundation model)

RadFM is an open generalist radiology foundation model that pairs a visual encoder with a large language model and is trained on interleaved image and text, so users can ask questions about a scan in plain language. The 2023 arXiv paper trained it on the 16M-scan MedMD dataset, and it handles CT, MRI and X-ray in both 2D and 3D with text prompts. It is a research system for groups exploring conversational or multimodal radiology assistants rather than a clinical product. Its accuracy is below specialist models on individual tasks, which is the central trade-off of generalist medical models, and oncology-specific evaluation is limited. For a newcomer: RadFM is an early attempt at a chatbot that can look at many kinds of scan, broad but not yet as good as dedicated tools.