The science
DeepSensi™ does not ask you to trust it. It gives you the derivation, the data, and the audit. The safety case is built the way aviation and nuclear engineering build theirs: with a quantified, worst-case bound.
Eight ideas, made rigorous
Twenty-three independent barriers modelled per IEC 61025, with a justified common-cause factor and worst-case degradation. The system-level bound is derived, not asserted. WP-001 →
Static benchmarks reward recall and punish caution. Auto-CSA scores the safe acknowledgement of uncertainty, and exposes benchmark defects openly. WP-002 →
The Gomola Framework gives clinical AI what aviation has had for decades: quantitative reliability tiers, five auditable pillars, royalty-free. DSS-001 →
A specialist agent for every discipline of medicine deliberates under cross-vendor verification, and physicians join as scored nodes. Verified insight earns outcome-gated royalties: the first formal economic model for clinical expertise inside an AI. WP-003 → WP-004 →
DeepSensi™ is built to make a clinician faster and safer, never to replace the signature. The judgment stays human; the machine carries the recall, the cross-checking, and the court-grade record. WP-003 →
The same engine reaches patients no specialist can: borderless matching to compassionate-access therapies, and physician-level epidemic early warning as a private by-product of ordinary care. WP-006 → WP-007 →
A temporal health graph that never forgets, and a digital twin that keeps watching after the visit ends. When reality diverges from the expected trajectory, the case reopens itself. Even the voice becomes a vital sign.
From a clinic gateway to a hospital node with the cable cut: the complete consilium and safety layer on premises. Nations keep their data. The field keeps its radar.
The benchmark, in context
DeepSensi: 86.0% top-1, 93.7% top-3 on 301 NEJM CPC cases (2014 to 2023), development-cohort, with a 0.0% missed-critical rate. Others, on NEJM CPC cases via SDBench: Nori et al. 2025 (304 cases, 21 US and UK physicians). 1 IEC 61508 SIL-4 demand-mode target. 2 development-cohort; a confirmatory study is designated.