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A Multimodal Foundation Model for Longitudinal Patient Representation and Scalable Insight Generation in Oncology

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Precision oncology necessitates a longitudinal model of patient state that captures cancer evolution and treatment over time, integrating multimodal observations. We introduce the oFM, a foundation model developed on a real-world oncology cohort of 1.67 million cancer patients that integrates clinical trajectories with DNA, RNA, and H&E pathology. Patient-level partitions were reserved for training, validation, and testing, with over one million patients used for training. The oFM encodes daily clinical and molecular episodes and, along with pathology images, integrates them over time to produ

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