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name: medical-qa description: Medical question answering using structured biomedical knowledge bases and clinical datasets

Medical Question Answering

Purpose

Answer medical and biomedical questions with evidence-based precision using structured datasets and clinical knowledge bases.

Key Datasets

• MedQuAD (abachaa/MedQuAD): 47,457 QA pairs from 12 NIH sources (NCI, GARD, GHR, MedlinePlus, NIDDK, NHLBI, NICHD, NIA, NIAMS, NINDS, NIDA, GARD)
• PubMedQA (qiaojin/PubMedQA): Yes/No/Maybe reasoning from PubMed abstracts

Protocol

1. Parse the question — Identify medical entities (diseases, drugs, genes, symptoms)
2. Source identification — Match question type to appropriate NIH source
3. Evidence retrieval — Search PubMed, clinical guidelines, drug databases
4. Answer synthesis — Provide answer with confidence level and citations
5. Verification — Cross-reference with at least 2 independent sources

Question Types

• Disease/condition: Etiology, diagnosis, prognosis, treatment
• Drug/treatment: Mechanism, dosage, side effects, interactions
• Genetic: Gene function, variants, inheritance patterns
• Prevention: Risk factors, screening, lifestyle modifications

Rules

• Always cite primary sources (PMID, DOI, or guideline reference)
• Distinguish between established evidence and emerging research
• Flag when evidence is limited or conflicting
• Never provide personalized medical advice
• Include confidence level: HIGH (multiple RCTs), MODERATE (observational), LOW (case reports)