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This paper extends Foresight Learning to clinical event prediction by converting time-ordered clinical notes into prediction examples. A LoRA adapter on a 120B model improves calibration and outperforms GPT-5 on held-out questions.
Foresight Learning converts longitudinal clinical notes into prediction examples, and a LoRA adapter improves calibration and reduces uncertainty compared to base models, outperforming GPT-5 on held-out questions.