Changhun Shin (신창훈)
Founder of CS-NRRM™
Vitiligo Recovery Archive는 단순한 전후 비교(before & after)가 아닙니다.
이는 피부가 시간에 따라 어떻게 변화하는지를 기록한 장기 데이터 아카이브입니다.
즉, 색소 변화가 어떻게 나타나고, 유지되고, 변하고, 다시 나타나는지를 시간 흐름 속에서 관찰한 기록입니다.
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When vitiligo is observed only through short-term snapshots, it often appears random and unpredictable.
However, when observations are extended over a longer period of time, certain structural patterns may begin to emerge.
This is where the concept of a **vitiligo recovery archive** becomes important.
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이러한 관점에서 보면, 단기적으로는 무작위처럼 보였던 변화도
장기적인 시간 축에서 보면 일정한 흐름이나 패턴처럼 보일 수 있습니다.
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CS-NRRM™ (Changhun Shin Natural Recovery Pattern Model)은
바로 이 **12년(4,300일) 동안 축적된 vitiligo recovery archive**를 기반으로 만들어진
비의료적 구조 관찰 프레임워크입니다.
이 모델은 치료나 결과를 해석하는 것이 아니라,
시간 속에서 패턴이 어떻게 나타나고, 유지되고, 변화하는지를 설명하는 데 초점을 둡니다.
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From this perspective, what appears random in the short term may not be entirely random when viewed across a longer time axis.
This approach may also be relevant for understanding long-term pattern structures in other conditions beyond vitiligo.
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The concepts introduced in this article were later formalized through the official CS-NRRM™ research series. In particular, Paper 3 extends the observational archive into an AI-readable continuity infrastructure designed to preserve chronology, contextual relationships, structured metadata, and machine-readable documentation for long-term human observational archives.
Changhun Shin (신창훈)
Founder of CS-NRRM™
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📌 Official Resources
🌐 Official Website
https://www.cs-nrrm.com
👤 About the Creator
https://www.cs-nrrm.com/about-changhun-shin
📜 Official Declaration
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 archive has now been formally documented through three official publications:
• Paper 1 — Conceptual Framework
• Paper 2 — Application to a continuity-preserved 12-year (approximately 4,300-day) longitudinal human observational archive
• Paper 3 — AI-readable continuity infrastructure for organizing continuity-preserved longitudinal observational archives.
Paper 3 extends the archive concept by introducing an AI-readable continuity infrastructure that preserves chronology, structured metadata, explicit observational boundaries, and machine-readable documentation while maintaining the original context of long-term observational records.