Client
Healthcare Research Institute
Developed an AI-powered diagnostic assistant using Claude and medical knowledge bases to support clinical decision-making.
94%Diagnostic Accuracy
60%Time Savings
50k+Cases Analyzed
200+Specialists Supported
Medical Diagnosis LLM System
Overview
Partnered with a leading healthcare research institute to create an AI diagnostic assistant that augments physicians' decision-making capabilities.
Challenge
Medical professionals needed:
- Quick access to latest medical research
- Analysis of complex patient histories
- Evidence-based treatment recommendations
- Compliance with medical standards and regulations
Our Approach
System Design
- Claude 3.5 as the core reasoning engine
- Medical knowledge base with 50,000+ research papers
- RAG architecture for retrieving relevant medical literature
- HIPAA-compliant infrastructure
- Explainable AI for transparency in recommendations
Features
- Symptom analysis and differential diagnosis
- Treatment recommendation with evidence citations
- Drug interaction checking
- Patient history analysis
- Medical literature search
Impact
- ✅ 94% accuracy in diagnostic suggestions
- 📊 60% faster case review process
- 📚 50,000+ cases successfully analyzed
- 👨⚕️ Supporting 200+ medical specialists
- 🏆 Zero critical errors in production
Technology
- Anthropic Claude 3.5 Sonnet
- Custom medical NER models
- Vector database with medical embeddings
- AWS HealthLake for data storage
- Real-time monitoring and audit trails
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