PDFMedicalEducationDataExtractionAI

MedPDF Structurer

Turn chart-heavy professional PDFs into queryable structured knowledge

Problem
A developer trying to structure the Chinese medical textbook Internal Medicine found that after splitting by table of contents, he got stuck on parsing images, tables, and flowcharts. AI-generated parsing scripts kept failing. In medical texts these diagrams carry diagnostic logic that is lost if dropped.
Solution
Upload a PDF, automatically split by chapter, extract tables/flowcharts/diagrams as structured fields. Provide disease-centric knowledge card templates and export JSON/CSV for downstream training or retrieval. Mark unparseable diagrams for human review rather than silently dropping them.
Users
Medical educators, developers building medical knowledge bases or question banks, med students preparing for exams
MVP
Only do chapter splitting + diagram OCR + table extraction; export disease cards; highlight unresolved areas; support local-only processing of sensitive material
Revenue
Per-document purchase or subscription; API billing for training institutions and med-exam platforms
Why now
LLM layout understanding is just good enough, but general tools still lose key diagrams in professional textbooks — a vertical gap an indie dev can own

Source discussions · 1

  1. V2EX[程序员] 我要结构化入库一本书《内科学 十四五 第十版.pdf》0↑ 4
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