deidentify
OfficialLLM-free PHI de-identification for clinical data.
AuthorAperivue
Version1.0.0
Installs0
System Documentation
What problem does it solve?
De-identify clinical research data before analysis by removing PHI using rule-based, locale-aware patterns and interactive review, without sending data to external models.
Core Features & Use Cases
- Locale-aware PHI detection: uses country-specific patterns and column-name heuristics to classify fields as PHI.
- Interactive review and anonymization: researchers approve pseudonymization, date shifting, and suppression in a guided terminal flow.
- Audit trail and mapping: produces a de-identified dataset plus a secure mapping file and an audit log for IRB compliance.
Quick Start
Run the deidentify tool on your dataset to produce a de-identified copy with an audit trail.
Dependency Matrix
Required Modules
openpyxl
Components
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: deidentify Download link: https://github.com/Aperivue/medsci-skills/archive/main.zip#deidentify Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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