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February 26, 20264 citationsOpen Access

GQMI: MedAI Trust-Graph (v0.2.3) — Audit-first haemodynamic design test and dynamic clinical consistency

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HSHisashi Suga

Key Points

  • To provide a governance framework for auditable haemodynamic design tests in medical AI.
  • Integrates audit-first governance with a trust-graph of the medical AI pipeline.
  • Incorporates a haemodynamic audit ledger for reproducibility as a contract.
  • Establishes a dynamic clinical consistency layer assessing stability under drift.
  • Introduces reproducibility protocols enforcing consistent outputs based on locked input conditions.
  • Enhances stability measures to ensure clinical consistency in design tests.

Abstract

What this is This release ships an audit-first, NO OVERCLAIM governance framework for Medical AI, integrating: M1: a trust-graph of the medical AI pipeline (fixed node IDs, trust-injection points, responsibility anchors), M2: a haemodynamic audit ledger that enforces reproducibility as a contract (same inputs + same BC + same solver config -> same outputs), M3: a dynamic clinical consistency layer (temporal coherence, causal plausibility, stability under drift/perturbation). What this is NOT This work is not clinical advice. It does not provide treatment recommendations, patient-specific guidance, or outcome claims. It is a governance and reproducibility protocol for auditable haemodynamic design tests (e. g. , bypass/stent geometry changes and their effect on flow/pressure/WSS) under locked boundary conditions and solver configuration. Files Main manuscript: PDF + DOCX. Figures: Fig. 1–3 (PNG). Supplementary Information: PDF + DOCX. INSTALLME: plain-text packing slip (how to read / what is locked / font policy). Version note v0. 2. 3 extends v0. 1 by adding M2 (haemodynamic audit ledger) and M3 (dynamic clinical consistency), plus Figures 1–3 and SI.

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Hisashi Suga (2026) studied this question.

synapsesocial.com/papers/699f956d1bc9fecf3dab321chttps://doi.org/10.5281/zenodo.18757326
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