LabLens AI – Intelligent Medical Data Extraction
A medical intelligence platform that transforms unstructured paper lab reports into structured, actionable data using Vision AI.
Focuses on robust extraction across varying lab layouts and produces clean biomarker outputs for downstream workflows.
Project Details
Technologies
Key Metrics
20+
Biomarkers
90%
Time Saved
99%
OCR Accuracy
The Problem
Traditional paper lab reports created a manual data entry bottleneck in clinical workflows. The primary challenge was the extreme variability in document layouts across different laboratory providers, which made consistent, high-accuracy extraction nearly impossible with standard OCR tools.
The Solution
We architected a robust Vision AI pipeline using Google Gemini to extract context-aware structured data directly from medical tables. By implementing an "Intelligence-First" approach, the system understands the semantic meaning of clinical biomarkers, ensuring data is mapped correctly regardless of the report layout.
Architecture & Implementation
- AI Pipeline: Google Gemini Vision integration for context-aware biomarker extraction.
- Resilience: Custom-built API Key Rotation system with automatic failover to bypass provider rate limits.
- Backend: Django REST Framework providing a secure, audit-logged API for clinical data management.
- Frontend: Next.js clinician dashboard with real-time progress tracking for batch uploads.
Results & Impact
Successfully automated the extraction of 20+ clinical biomarkers with 99% accuracy. The implementation reduced manual entry time by 90%, allowing clinicians to focus on patient outcomes rather than administrative data transcription.