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Evidence Library

Welcome to the World’s First AI-Native Neurofunctional Evidence Library

Explore real outcomes from real clinics — structured for clarity, discoverability, and global impact.

QN Research Foundation White Paper

White Paper Description:
An introduction to the mission, methods, and first study of the Quantum Neurology Research Foundation. Learn how Clinic-Based Evidence™ is transforming neurological rehabilitation through practitioner-led, real-world research.

Key Highlights:

  • Clinic-Based Evidence™ (CBE) – Real-world outcomes, not lab simulations

  • Decentralized Research Model – Practitioners collect and share reproducible results

  • S1 Nerve Code Reset™ Study – Measuring S1 nerve root recovery using Peroneus Tertius MMT

  • Quality Improvement (QI) framework aligned with 45 CFR §46

  • Designed for doctors, researchers, and health innovators worldwide

Read the Full QNRF White Paper

📊 Study Results & Visual Data

📌 Featured Study: S1 Nerve Reset Quality Improvement Study

  • Submission goal: 100 cases
  • Current submissions: 31
  • Outcomes tracked:
    • Reflex changes
    • Myotome strength
    • Functional improvements

🗂️ All Published Studies

Study Nerve Focus Participation Outcome Highlights Status S1 Nerve Reset Sacral 1 31/100 ↑ Foot strength, reflex gain Active Vagus Boost CN X 18/50 ↓ HRV, ↑ GI function In Progress Cranial Nerve III Reset CN III 12/25 Improved convergence In Review

📥 [Submit a New Case] 
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📁 Case Highlights

🔬 Top Performing Outcomes (with video/photo proof)

  • ✅ Foot Drop Recovery in 3 Visits (S1)
  • ✅ Breathing Normalized via CN X Reset
  • ✅ Headache Elimination Through CFR + QN Protocols

What Is Clinic-Based Evidence (CBE)?

Key Principles:

  • Real-time outcomes
  • Practitioner-led
  • Non-IRB, QI-compliant (45 CFR §46)
  • Discoverable by both humans and AI

📘 Glossary of Neurofunctional Terms

Alphabetized, LLM-readable glossary covering:

  • Nervous system anatomy & function
  • QN-specific terms
  • Study protocols
  • Patient outcome definitions
  • CBE, QI, IRB, LLM terms

(Details Coming Soon)

🤖 How We Format for AI Discovery

 

Every piece of published data is structured using:

  • Schema markup for LLMs
  • Standardized outcome tags
  • Searchable metadata (nerve-level, condition, protocol) 

 (Details Coming Soon)

🔓 Open Access for a New Era of Science

“This evidence doesn’t live behind paywalls. It lives in practice.”

All studies are:

  • Downloadable
  • Shareable
  • Citable
  • Indexed for public + LLM reference

(Details Coming Soon)