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Skill

cgm-analyzer

by zinojeng

AI Summary

CGM Analyzer is a diabetes management tool that processes continuous glucose monitor data from multiple devices, calculates clinical metrics (TIR/TAR/TBR), generates visualizations, and provides AI-powered recommendations. It benefits diabetes patients, healthcare providers, and developers building glucose management applications.

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to install the "cgm-analyzer" skill in my project.

Please run this command in my terminal:
# Install skill into the correct directory
mkdir -p .claude/skills/cgm_skill && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/cgm_skill/SKILL.md "https://raw.githubusercontent.com/zinojeng/cgm_skill/main/skill.md"

Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.

Description

Analyzes continuous glucose monitor CSV data, calculates TIR/TAR/TBR metrics, generates AGP charts, and provides AI-powered diabetes management recommendations. Handles Dexcom, FreeStyle Libre, Guardian formats.

📁 技能檔案結構

` cgm_skill/ ├── skill.md # 主要技能文檔 ├── config.yaml # 配置檔案 ├── VERSION # 版本號 ├── CHANGELOG.md # 變更日誌 ├── README.md # 使用說明 ├── knowledge/ # 專業知識庫(模組化) │ ├── cgm_metrics.md # 基礎 CGM 指標 │ ├── diabetes_guidelines.md # 糖尿病管理指南 │ ├── metrics/ # 指標詳細文檔 │ │ ├── tir_targets.md # TIR 目標值 │ │ └── variability.md # 變異性指標 │ ├── populations/ # 族群特定指南 │ │ └── pregnancy.md # 妊娠期指南 │ └── treatments/ # 治療相關資訊 ├── scripts/ # 可執行腳本(已設定執行權限) │ ├── split_csv.py # CSV 檔案分割工具 │ ├── analyze_cgm.py # CGM 數據分析工具 │ ├── llm_analysis.py # LLM 智能分析報告生成器 │ ├── validate.py # 數據驗證工具 │ ├── setup.py # 互動式設定精靈 │ ├── batch_process.py # 批次處理工具 │ ├── test_skill.py # 自我測試工具 │ └── requirements.txt # Python 依賴套件 └── examples/ # 範例數據和文檔 ├── sample_cgm_data.csv # 範例 CGM 數據 └── README.md # 範例使用說明 `

功能概述

這是一個專門處理連續血糖監測(Continuous Glucose Monitor, CGM)數據的智能分析技能。可以從 CSV 格式的原始 CGM 數據中提取關鍵資訊,進行多維度分析,並生成專業的醫療建議報告。

1. 數據處理與解析

• CSV 文件讀取:自動解析包含日期、時間、血糖值的 CGM 數據文件 • 數據清理:處理缺失值、異常值,確保數據品質 • 時間序列轉換:將原始數據轉換為時間序列格式,便於分析 • 事件提取:識別並分析用餐、胰島素注射等事件標記

2. 血糖指標計算

• Time in Range (TIR):計算血糖在目標範圍內的時間百分比 • 變異係數 (CV):評估血糖波動程度 • 平均血糖 (Mean Glucose):計算觀察期間的平均血糖值 • GMI (Glucose Management Indicator):估算糖化血紅蛋白 (HbA1c) • GRI (Glycemic Risk Index):綜合評估血糖風險 • 低血糖/高血糖時間:統計血糖異常的時間分布

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Health Signals

MaintenanceCommitted 5mo ago
Stale
AdoptionUnder 100 stars
0 ★ · Niche
DocsREADME + description
Well-documented

GitHub Signals

Forks1
Issues0
Updated5mo ago
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Works With

Claude Code