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Case StudyTier BPrototypeSpring 2023
Bilingual Semantic Medicine Search
Persian/English semantic retrieval prototype built from Iranian FDA and WHO ATC data.
AIDataResearch
Context
Spring 2023 · Academic prototype · Maturity: Prototype.
Problem
Users needed cross-language semantic retrieval over medicine data rather than exact keyword matching.
Users
Academic prototype context.
My Role
Academic NLP product/implementation.
Product Decisions & Responsibilities
- Framed the system as information retrieval, not medical advice.
Technical Approach
- Built a 65,469-record combined dataset and bilingual semantic retrieval flow.
NLPSemantic searchIranian FDA dataWHO ATC data
Constraints
- No comprehensive trustworthy F1/accuracy metric in current evidence.
- Healthcare domain requires careful scope.
Product Flow
- Prepare FDA/WHO data
- Normalize bilingual fields
- Encode/index
- Semantic query
- Return ranked records
Outcome
- Final dataset contained 65,469 records.
What I Learned
- In high-stakes domains, defining what the product does not do is part of product design.
Evidence Boundary
What this does — and does not — prove
Retrieval prototype only — not diagnosis, prescription, or treatment recommendation.
Next Iteration
Extend the product only after the next decision can be tied to stronger user, operational, or business evidence rather than adding features for their own sake.