HaHafeng
beb7f7f559
Core Components: - PDFStorageService with Dify/OSS adapters - LLM12FieldsService with Nougat-first + dual-model + 3-layer JSON parsing - PromptBuilder for dynamic prompt assembly - MedicalLogicValidator with 5 rules + fault tolerance - EvidenceChainValidator for citation integrity - ConflictDetectionService for dual-model comparison Prompt Engineering: - System Prompt (6601 chars, Section-Aware strategy) - User Prompt template (PICOS context injection) - JSON Schema (12 fields constraints) - Cochrane standards (not loaded in MVP) Key Innovations: - 3-layer JSON parsing (JSON.parse + json-repair + code block extraction) - Promise.allSettled for dual-model fault tolerance - safeGetFieldValue for robust field extraction - Mixed CN/EN token calculation Integration Tests: - integration-test.ts (full test) - quick-test.ts (quick test) - cached-result-test.ts (fault tolerance test) Documentation Updates: - Development record (Day 2-3 summary) - Quality assurance strategy (full-text screening) - Development plan (progress update) - Module status (v1.1 update) - Technical debt (10 new items) Test Results: - JSON parsing success rate: 100% - Medical logic validation: 5/5 passed - Dual-model parallel processing: OK - Cost per PDF: CNY 0.10 Files: 238 changed, 14383 insertions(+), 32 deletions(-) Docs: docs/03-涓氬姟妯″潡/ASL-AI鏅鸿兘鏂囩尞/05-寮€鍙戣褰?2025-11-22_Day2-Day3_LLM鏈嶅姟涓庨獙璇佺郴缁熷紑鍙?md
109 lines
2.0 KiB
Markdown
109 lines
2.0 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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