New preprint from
@lightningrodai!
We trained AI to predict clinical events — ICU transfers, new diagnoses, complications, procedures, ventilation, mortality — directly from raw clinical notes.
No labeled data required – 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:
🎯 ~70% lower calibration error
📈 Brier skill score: ~0% → 27%
🧠 84% win-rate vs the base model in blind reasoning review
🥇 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 —
@indiequant @KSkotheim64001 🙌
Full paper 👇
arxiv.org/abs/2605.12817