The week's most disruptive science, explained for humans.

How Deep is the Signal? Time-Context up to 30 Years for Colorectal Cancer Prediction in a Primary-Care EHR Model

A 30-year lookback in a London primary-care model lifts colorectal-cancer AUROC from 0.551 to 0.590, and most of that gain arrives within ten years.

• ▸What: The authors pretrain a 34.6-million-parameter decoder on 1.4 billion coded events from 3.6 million North West London patients, then test colorectal-cancer prediction on the same 1,008 cases and 9,582 matched controls at 15 nested lookbacks from 2 to 30 years.
• ▸Why it matters: EHR foundation models have been sold on token context. If time-context is a separate design axis, clinics may be keeping decades of records for a discrimination gain that mostly saturates in a decade, and rotary embeddings may alias beyond about 20 years.
• ▸Who should care: Clinical-prediction teams, EHR-foundation-model builders, health-system data officers deciding how far back to store identifiable events, and anyone scoring medical AI as if longer context were automatically better.