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Healthcare AI-Based Decision Support System
Architected a multi-step LLM-powered clinical decision support platform that transforms patient records and medical guidelines into structured diagnostic workflows.
The system combines OCR processing, patient-data ingestion, AI-powered reasoning, and human-in-the-loop validation to improve reliability and consistency of clinical recommendations.
Key contributions included:
• Designing the LLM decision-engine architecture
• Building medical guideline-to-decision-tree workflows
• Developing evaluation and review tooling for quality assurance
• Integrating OCR and patient-data processing pipelines
• Supporting orchestration across multiple AI and healthcare system components
Technologies: Python, LLMs, OCR, Workflow Orchestration, Healthcare AI
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