HaHafeng
e3e7e028e8
Platform Infrastructure - 8 Core Modules Completed: - Storage Service (LocalAdapter + OSSAdapter stub) - Logging System (Winston + JSON format) - Cache Service (MemoryCache + Redis stub) - Async Job Queue (MemoryQueue + DatabaseQueue stub) - Health Check Endpoints (liveness/readiness/detailed) - Database Connection Pool (with Serverless optimization) - Environment Configuration Management - Monitoring Metrics (DB connections/memory/API) Key Features: - Adapter Pattern for zero-code environment switching - Full backward compatibility with legacy modules - 100% test coverage (all 8 modules verified) - Complete documentation (11 docs updated) Technical Improvements: - Fixed duplicate /health route registration issue - Fixed TypeScript interface export (export type) - Installed winston dependency - Added structured logging with context support - Implemented graceful shutdown for Serverless - Added connection pool optimization for SAE Documentation Updates: - Platform infrastructure planning (04-骞冲彴鍩虹璁炬柦瑙勫垝.md) - Implementation report (2025-11-17-骞冲彴鍩虹璁炬柦瀹炴柦瀹屾垚鎶ュ憡.md) - Verification report (2025-11-17-骞冲彴鍩虹璁炬柦楠岃瘉鎶ュ憡.md) - Git commit guidelines (06-Git鎻愪氦瑙勮寖.md) - Added commit frequency rules - Updated 3 core architecture documents Code Statistics: - New code: 2,532 lines - New files: 22 - Updated files: 130+ - Test pass rate: 100% (8/8 modules) Deployment Readiness: - Local environment: 鉁?Ready - Cloud environment: 馃攧 Needs OSS/Redis dependencies Next Steps: - Ready to start ASL module development - Can directly use storage/logger/cache/jobQueue Tested: Local verification 100% passed Related: #Platform-Infrastructure
101 lines
1.9 KiB
Markdown
101 lines
1.9 KiB
Markdown
# DC - 数据清洗整理
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> **模块代号：** DC (Data Cleaning)
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> **开发状态：** ⏳ 规划中
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> **商业价值：** ⭐⭐⭐⭐⭐ 可独立售卖
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> **独立性：** ⭐⭐⭐⭐⭐
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> **优先级：** P1
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---
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## 📋 模块概述
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数据清洗整理模块提供专业工具，处理医院导出的海量（百万行级）、多表格的Excel数据。
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**核心价值：** 核心差异化功能，解决医学科研痛点
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---
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## 🎯 核心功能
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### 1. 表格ETL（重点）
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- 多张Excel表格导入
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- 按"患者ID"和"时间"自动JOIN
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- 重组为干净的分析宽表
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### 2. 文本提取（NER）（重点）
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- 从病理报告提取结构化字段
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- 从住院小结提取关键信息
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- TNM分期自动识别
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### 3. 数据质量报告
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- 缺失值统计
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- 异常值检测
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- 数据质量评分
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### 4. 导出标准化数据
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- Excel导出
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- SPSS格式
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- R语言格式
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---
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## 📂 文档结构
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```
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DC-数据清洗整理/
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├── [AI对接] DC快速上下文.md # ⏳ 待创建
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├── 00-项目概述/
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│ └── 01-产品需求文档(PRD).md # ⏳ 待创建
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├── 01-设计文档/
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│ ├── 01-ETL引擎设计.md # ⏳ 待创建
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│ └── 02-医学NLP设计.md # ⏳ 待创建
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└── README.md # ✅ 当前文档
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```
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---
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## 🔗 依赖的通用能力
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- **LLM网关** - 医学NER提取（云端版）
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- **文档处理引擎** - Excel/Docx读取
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- **ETL引擎** - 数据清洗和转换
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- **医学NLP引擎** - 实体识别（单机版）
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---
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## 🎯 商业模式
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**目标客户：** 临床科室、数据管理员
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**售卖方式：** 独立产品
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**定价策略：** 按项目数或一次性License
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---
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## ⚠️ 技术难点
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1. **大数据处理** - 百万行数据的内存管理
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2. **隐私保护** - 单机版必须100%本地化
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3. **NER准确率** - 医学术语复杂
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---
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**最后更新：** 2025-11-06
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**维护人：** 技术架构师
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