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AIclinicalresearch/docs/03-业务模块/SSA-智能统计分析/README.md
HaHafeng 8eef9e0544 feat(asl): Complete Week 4 - Results display and Excel export with hybrid solution
Features:
- Backend statistics API (cloud-native Prisma aggregation)
- Results page with hybrid solution (AI consensus + human final decision)
- Excel export (frontend generation, zero disk write, cloud-native)
- PRISMA-style exclusion reason analysis with bar chart
- Batch selection and export (3 export methods)
- Fixed logic contradiction (inclusion does not show exclusion reason)
- Optimized table width (870px, no horizontal scroll)

Components:
- Backend: screeningController.ts - add getProjectStatistics API
- Frontend: ScreeningResults.tsx - complete results page (hybrid solution)
- Frontend: excelExport.ts - Excel export utility (40 columns full info)
- Frontend: ScreeningWorkbench.tsx - add navigation button
- Utils: get-test-projects.mjs - quick test tool

Architecture:
- Cloud-native: backend aggregation reduces network transfer
- Cloud-native: frontend Excel generation (zero file persistence)
- Reuse platform: global prisma instance, logger
- Performance: statistics API < 500ms, Excel export < 3s (1000 records)

Documentation:
- Update module status guide (add Week 4 features)
- Update task breakdown (mark Week 4 completed)
- Update API design spec (add statistics API)
- Update database design (add field usage notes)
- Create Week 4 development plan
- Create Week 4 completion report
- Create technical debt list

Test:
- End-to-end flow test passed
- All features verified
- Performance test passed
- Cloud-native compliance verified

Ref: Week 4 Development Plan
Scope: ASL Module MVP - Title Abstract Screening Results
Cloud-Native: Backend aggregation + Frontend Excel generation
2025-11-21 20:12:38 +08:00

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# SSA - 智能统计分析
> **模块代号:** SSA (Smart Statistical Analysis)
> **开发状态:** ⏳ 规划中
> **商业价值:** ⭐⭐⭐⭐⭐ 刚需
> **独立性:** ⭐⭐⭐⭐
> **优先级:** P2
---
## 📋 模块概述
智能统计分析模块提供3条核心分析路径实现从数据上传到报告导出的完整流程。
---
## 🎯 核心功能3条路径
### 1. 队列研究分析
- 基线特征分析
- 生存分析Kaplan-Meier
- Cox回归
### 2. 预测模型构建
- 变量筛选
- 模型构建Logistic回归、随机森林
- 模型验证ROC曲线
### 3. RCT研究分析
- 随机化检查
- 疗效分析
- 亚组分析
---
## 📂 文档结构
```
SSA-智能统计分析/
├── [AI对接] SSA快速上下文.md # ⏳ 待创建
├── 00-项目概述/
│ └── 01-产品需求文档(PRD).md # ⏳ 待创建
└── README.md # ✅ 当前文档
```
---
## 🔗 依赖的通用能力
- **文档处理引擎** - 数据导入
- **ETL引擎** - 数据预处理
---
## 🏗️ 技术栈
- **R语言** - 统计分析核心
- **Plumber** - R暴露为API
- **Node.js** - 粘合层
---
## 🎯 商业模式
**与ST模块协同售卖**
---
**最后更新:** 2025-11-06
**维护人:** 技术架构师