Preprint
SENTINEL: A Mid-Reasoning Interception Framework for Auditing Medical AI Agents in Production
Andrew Espira · 2026-05-31
Zenodo preprint
ORCID: https://orcid.org/0009-0002-9196-8094 · DOI: 10.5281/zenodo.21724763
Abstract
As medical AI agents accelerate administrative and clinical workflows, their speed advantage introduces a structural risk: agents can reason incorrectly faster than humans can intervene. We present SENTINEL, a mid-reasoning interception framework that audits agent reasoning traces before irreversible healthcare decisions are executed, gating actions through confidence tiers across an MCP-based healthcare RCM platform.
Cite
Andrew Espira (2026). SENTINEL: A Mid-Reasoning Interception Framework for Auditing Medical AI Agents in Production. Zenodo preprint. https://doi.org/10.5281/zenodo.21724763
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