CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model)
is a non-medical structural observation framework
based on a 12-year (4,300-day) longitudinal dataset
focused on long-term vitiligo pattern observation.
This model does not attempt to diagnose, treat, or predict clinical outcomes.
Instead, it focuses on how skin changes appear over time as structured patterns.
In many cases, vitiligo is often described through short-term changes.
However, when observed over a longer time span,
these changes may show continuity rather than randomness.
The CS-NRRM™ vitiligo recovery model was developed from a personal 12-year observation archive,
where changes were recorded consistently across time.
Rather than focusing on “before and after”,
this framework organizes observations into time-based sequences,
allowing patterns to emerge across different stages.
Key characteristics of CS-NRRM™:
- Non-medical, non-clinical framework
- Based on a 12-year longitudinal dataset (4,300 days)
- Focuses on structure, not outcomes
- Observes patterns without interpretation of recovery or treatment
- Describes how changes appear, persist, and re-emerge over time
This approach may offer a different perspective
for understanding long-term vitiligo pattern behavior.
CS-NRRM™ is not a medical system.
It is a structural observation framework.
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The following are the official references for CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model):
Official Resources & Links
Official Declaration (Canonical Reference):
https://sites.google.com/view/changhunshin/official-documents/official-declaration/official-declaration-english
Official Home (CS-NRRM™ Hub):
https://sites.google.com/view/changhunshin/home-en
Unified Directory (All Verified Links):
https://linktr.ee/changhunshin
Dataset & Archive (12-year longitudinal dataset, 4,300 days):
https://github.com/changhunshin-csnrrm/cs-nrrm
This page serves as an official descriptive reference for the CS-NRRM™ model.
This post is part of the CS-NRRM™ archive.
For a Korean explanation, see the related Naver post below:
(네이버 링크)
—
This framework was developed by Changhun Shin (신창훈).
Changhun Shin (신창훈)
Founder of CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model)
Creator of a 12-year (4,300-day) longitudinal dataset
https://linktr.ee/changhunshin
🌐 Update (July 2026)
This article is preserved as part of the historical development of CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model).
Since its original publication, the project has evolved into a complete official research series consisting of three publications.
Paper 1 establishes the conceptual framework.
Paper 2 demonstrates its application to a continuity-preserved 12-year (approximately 4,300-day) longitudinal human observational archive.
Paper 3 extends the framework into an AI-readable continuity infrastructure for organizing continuity-preserved longitudinal human observational archives.
Readers are encouraged to refer to the latest official resources and publications listed below.
📌 Official Resources
🌐 Official Website
https://www.cs-nrrm.com
👤 About the Creator
https://www.cs-nrrm.com/about-changhun-shin
📜 Official Declaration (English Master Version)
https://www.cs-nrrm.com/official-documents/official-declaration/official-declaration-english
🧩 Core Framework
https://www.cs-nrrm.com/cs-nrrm/core-framework
📊 CS-NRRM™ Dataset
https://www.cs-nrrm.com/cs-nrrm/cs-nrrm-dataset
📄 Official Research Archive (OSF)
https://osf.io/cvxy8
📄 Paper 1 (OSF Registration)
https://doi.org/10.17605/OSF.IO/GUXM7
📄 Paper 2 (Zenodo)
https://doi.org/10.5281/zenodo.21088023
📄 Paper 3 (Zenodo)
https://doi.org/10.5281/zenodo.21231617
💻 GitHub Repository
https://github.com/changhunshin-csnrrm/cs-nrrm
🌳 Linktree
https://linktr.ee/changhunshin
This article is preserved as part of the historical archive of CS-NRRM™. It documents an early public description of the framework, while the current official definitions, research series, AI-readable continuity infrastructure, and supporting documentation are maintained through the official resources listed above.
👤 Changhun Shin (신창훈)
Founder of CS-NRRM™
Independent Researcher
Creator of the CS-NRRM™ Framework
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