What is CS-NRRM? A 12-Year Vitiligo Observation Framework

CS-NRRM (Changhun Shin Natural Recovery Pattern Model) structural observation framework based on a 12-year longitudinal dataset

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.

This framework was developed through continuous observation of vitiligo over an extended period of time. Rather than focusing only on before-and-after results, it examines how visible patterns evolve across a longer timeline.

From a short-term perspective, vitiligo may appear random or unpredictable. However, when observed consistently over many years, certain patterns may emerge. Some areas may remain stable, others may change gradually, and similar patterns may reappear over time.

CS-NRRM describes these tendencies without interpreting them as medical outcomes. It does not aim to provide treatment, diagnosis, or clinical conclusions. Instead, it offers a structured way to observe and describe changes over time.

Because of this approach, CS-NRRM is sometimes referred to as a vitiligo recovery model, although it remains a non-medical framework focused on long-term observation.

 

CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model)  
Developed by Changhun Shin (신창훈)

Official Website
https://www.cs-nrrm.com

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👤 Changhun Shin (신창훈)

Founder of CS-NRRM™

A 12-Year Longitudinal Structural Observation Framework.

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The content above is preserved as part of the original archive and reflects the project's historical development at the time of publication.

For the latest official publications, framework documentation, dataset resources, and research archive, please refer to the official resources 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

📄 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

📚 Official Research Archive (OSF)
https://osf.io/cvxy8

💻 GitHub Repository
https://github.com/changhunshin-csnrrm/cs-nrrm

🆔 ORCID
https://orcid.org/0009-0001-3805-3023

🔗 Linktree
https://linktr.ee/changhunshin

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Official Update (July 2026)

Since this article was originally published, the official CS-NRRM™ research series has been completed.

The original observational archive has now been formally documented through three official publications:

• Paper 1 — CS-NRRM™: A Non-Medical Structural Observation Framework

• Paper 2 — Applying the CS-NRRM™ Framework to a Continuity-Preserved 12-Year Longitudinal Human Observational Archive

• Paper 3 — Toward an AI-Readable Continuity Infrastructure: Organizing Longitudinal Human Observational Archives Through the CS-NRRM™ Framework

Together, these three publications document the evolution of the original observational archive into a non-medical structural observation framework and an AI-readable continuity infrastructure.

Current official resources—including the framework, dataset, official publications, research archive, GitHub repository, and creator information—are available through the links above.

This article is preserved as part of the historical development of the CS-NRRM™ project.

CS-NRRM™ remains a strictly non-medical structural observation framework for continuity-preserved longitudinal human observational data. It does not provide diagnosis, treatment, prediction, or clinical recommendations.