HaHafeng
8eef9e0544
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
28 lines
670 B
TypeScript
28 lines
670 B
TypeScript
import XLSX from 'xlsx';
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const filePath = 'D:\\MyCursor\\AIclinicalresearch\\docs\\03-业务模块\\ASL-AI智能文献\\05-测试文档\\03-测试数据\\screening\\Test Cases.xlsx';
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const workbook = XLSX.readFile(filePath);
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const sheetName = workbook.SheetNames[0];
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const worksheet = workbook.Sheets[sheetName];
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const data = XLSX.utils.sheet_to_json(worksheet);
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console.log(`总行数: ${data.length}`);
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console.log('\n前3行数据:');
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data.slice(0, 3).forEach((row: any, i) => {
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console.log(`\n第${i+1}行:`);
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console.log(JSON.stringify(row, null, 2));
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});
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console.log('\n所有列名:');
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if (data.length > 0) {
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console.log(Object.keys(data[0]));
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}
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