New preprint from
@lightningrodai!
We trained AI to predict clinical events â ICU transfers, new diagnoses, complications, procedures, ventilation, mortality â directly from raw clinical notes.
No labeled data required â Foresight Learning infers outcomes from what happens later in patient records.
Using Tinker from
@thinkymachines , we trained a lightweight adapter on GPT-OSS-120B, resulting in a specialized predictor that runs on a single GPU.
Results:
đ¯ ~70% lower calibration error
đ Brier skill score: ~0% â 27%
đ§ 84% win-rate vs the base model in blind reasoning review
đĨ Slightly better Brier than GPT-5, despite being a fraction of the size
Hospitals and specialty clinics often treat unique patient populations that out-of-the-box models don't have training data for. This makes it possible to build frontier-quality predictors for highly specific patient groups, with nothing but raw clinical records.
Congrats to the team â
@indiequant @KSkotheim64001 đ
Full paper đ