The closed loop is the product
Evidence on risk models, preference influence, and surgical data abstraction points to one architecture: connect prediction, communication, adjudication, outcomes, and recalibration.
Archive
Neurosurgery AI Brief
Research, clinical tools and evidence boundaries in neurosurgical AI.
All 14 issues
The model is not a neutral renderer
Aneurysm benchmarks, shadow-mode deployment, and prediction studies show why base-model choice, temporal contracts, and clinical go/no-go thresholds are safety variables.
Topics for Issue 13
Clinical AI should be built for staged deployment
UK regulatory proposals and new clinical evidence point to one architecture: controlled deployment, versioned evidence, clinician handoff, and continuous monitoring.
Topics for Issue 12
Will AI make doctors worse at thinking?
The first essay in The Deskilling Question separates automation bias, cognitive offloading, and actual skill loss—and asks how clinical AI should preserve independent judgment.
Topics for Issue 11
The generative interface is becoming a regulatory object
FDA’s GenAI device discussion paper shows why variable outputs, clinician review, patient understanding, and postmarket monitoring are becoming product-design questions.
Topics for Issue 10
Who watches the clinical agent?
New spine and perioperative evidence, plus a neurosurgical observability proposal, show why clinical AI needs a safety layer separate from generation.
Topics for Issue 9
Clinical credibility is the moat
Live surgical AI, a stroke-edema device pathway, and new spine evidence show why the complete clinical system is the defensible asset.
Topics for Issue 8
Decoding is not independence
The first BCI Watch separates remarkable decoding results from evidence of durable, real-world functional independence.
Topics for Issue 7
Deployment is the evidence gap
Real surgical triage, weak prediction-model evidence, and the 2.5% trial problem define the next validation agenda.
Topics for Issue 6
From benchmarks to clinical competency
FDA’s discussion framework, new spine evidence, and why clinical AI must prove competency inside its intended workflow.
Topics for Issue 5
The model is replaceable. The clinical system is not.
Deployment surveillance, patient comprehension, corpus-specific RAG, and the architecture that makes clinical AI defensible.
Topics for Issue 4
AI that knows when to defer
Risk prediction, consent agents, clinical workflow, and the case for formal deferral in safety-critical neurosurgical AI.
Topics for Issue 3
External validation changes the conversation
Why honest external performance, simple models, and completeness checks matter more than impressive demonstrations.
Topics for Issue 2
The risk-and-consent copilot, not the AI neurosurgeon
A defensible architecture for risk prediction, consent preparation, workflow support, and substantive surgeon oversight.