family-health-analyzer

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

家庭健康分析技能

Family Health Analysis Skill

技能概述

Skill Overview

本技能提供家庭健康数据的深度分析,包括:

遗传风险评估
家族疾病模式识别
家庭共同问题分析
个性化预防建议
可视化报告生成

This skill provides in-depth analysis of family health data, including:

Genetic risk assessment
Family disease pattern identification
Analysis of common family health issues
Personalized prevention recommendations
Visual report generation

触发条件

Trigger Conditions

当用户请求以下内容时,使用此技能:

"家庭健康报告"
"家族病史分析"
"遗传风险评估"
"家庭健康趋势"
执行
```
/family report
```
命令
执行
```
/family risk
```
命令

Use this skill when the user requests:

"Family health report"
"Family medical history analysis"
"Genetic risk assessment"
"Family health trends"
Execute the
```
/family report
```
command
Execute the
```
/family risk
```
command

分析步骤

Analysis Steps

步骤1: 确定分析目标

Step 1: Define Analysis Objectives

识别用户请求类型:

家族病史分析
遗传风险评估
家庭健康趋势
家庭健康报告

Identify the type of user request:

Family medical history analysis
Genetic risk assessment
Family health trends
Family health report

步骤2: 读取家庭数据

Step 2: Read Family Data

数据源:

主数据文件:
```
data/family-health-tracker.json
```

集成模块数据:

```
data/hypertension-tracker.json
```
```
data/diabetes-tracker.json
```
```
data/profile.json
```

Data Sources:

Main data file:
```
data/family-health-tracker.json
```

Integrated module data:

```
data/hypertension-tracker.json
```
```
data/diabetes-tracker.json
```
```
data/profile.json
```

步骤3: 数据验证与清洗

Step 3: Data Validation and Cleaning

验证项目:

关系完整性
年龄合理性
数据一致性

Validation Items:

Relationship integrity
Age rationality
Data consistency

步骤4: 遗传模式识别

Step 4: Genetic Pattern Recognition

识别算法:

家族聚集性分析
遗传模式识别
早发病例识别(通常<50岁)

Recognition Algorithms:

Family aggregation analysis
Genetic pattern recognition
Early onset case identification (typically <50 years old)

步骤5: 风险计算算法

Step 5: Risk Calculation Algorithm

加权计算:

python

遗传风险评分 = (一级亲属患病数 × 0.4) +
              (早发病例数 × 0.3) +
              (家族聚集度 × 0.3)

风险等级:
- 高风险: ≥70%
- 中风险: 40%-69%
- 低风险: <40%

Weighted Calculation:

python

Genetic risk score = (Number of affected first-degree relatives × 0.4) +
              (Number of early onset cases × 0.3) +
              (Family aggregation degree × 0.3)

Risk levels:
- High risk: ≥70%
- Medium risk: 40%-69%
- Low risk: <40%

步骤6: 生成预防建议

Step 6: Generate Prevention Recommendations

建议分类:

筛查建议:定期检查项目
生活方式建议:饮食、运动、作息
就医建议:何时就医、咨询专科

示例:

json

{
  "category": "screening",
  "action": "定期血压监测",
  "frequency": "每周3次",
  "start_age": 35,
  "priority": "high"
}

Recommendation Categories:

Screening recommendations: Regular check-up items
Lifestyle recommendations: Diet, exercise, daily routine
Medical consultation recommendations: When to see a doctor, specialist consultation

Example:

json

{
  "category": "screening",
  "action": "Regular blood pressure monitoring",
  "frequency": "3 times a week",
  "start_age": 35,
  "priority": "high"
}

步骤7: 生成可视化报告

Step 7: Generate Visual Report

HTML报告组件:

家谱树(ECharts树图)
遗传风险热力图
疾病分布饼图
预防建议时间线

HTML Report Components:

Family tree (ECharts tree diagram)
Genetic risk heatmap
Disease distribution pie chart
Prevention recommendation timeline

步骤8: 输出结果

Step 8: Output Results

输出格式:

文本报告(简洁版):命令行输出
HTML报告(完整版):可视化图表

Output Formats:

Text report (concise version): Command-line output
HTML report (full version): Visual charts

安全原则

Safety Principles

医学安全边界

Medical Safety Boundaries

✅ 仅基于家族病史进行统计分析
✅ 提供预防建议和筛查提醒
✅ 明确标注不确定性
❌ 不进行遗传疾病诊断
❌ 不预测个体发病概率
❌ 不推荐具体治疗方案

✅ Only conduct statistical analysis based on family medical history
✅ Provide prevention recommendations and screening reminders
✅ Clearly indicate uncertainties
❌ Do not diagnose genetic diseases
❌ Do not predict individual onset probability
❌ Do not recommend specific treatment plans

免责声明

Disclaimer

每次分析输出必须包含:

⚠️ 免责声明:
1. 本分析基于家族病史统计,仅供参考
2. 遗传风险评估不预测个体发病
3. 所有医疗决策请咨询专业医师
4. 遗传咨询建议咨询专业遗传咨询师

Every analysis output must include:

⚠️ Disclaimer:
1. This analysis is based on family medical history statistics and is for reference only
2. Genetic risk assessment does not predict individual onset of disease
3. All medical decisions should be consulted with a professional physician
4. For genetic counseling, it is recommended to consult a professional genetic counselor

集成现有模块

Integrate Existing Modules

读取高血压管理数据
读取糖尿病管理数据
关联用药记录

技能版本: v1.0 最后更新: 2025-01-08 维护者: WellAlly Tech

Read hypertension management data
Read diabetes management data
Correlate medication records

Skill Version: v1.0 Last Updated: 2025-01-08 Maintainer: WellAlly Tech