About This Project
A state-of-the-art clinical AI assistant crafted to empower medical professionals with rapid, accurate, and compliant preliminary diagnostic intelligence.
The Technical Challenge
Clinical teams faced severe backlogs in reviewing high-volume radiology scans during peak emergency hours, delaying critical triage decisions.
Zavelin Engineering Solution
Built a GPU-accelerated YOLO & PyTorch deep learning pipeline paired with autonomous triage reasoning agents that deliver sub-second preliminary diagnostic support.
Quantifiable Impact Metrics
98.4%Diagnostic AccuracyClinical benchmark precision
3.5x FasterTriage VelocityReduction in patient wait times
< 150msInference LatencyHigh-speed model execution
Key Deliverables
YOLO Computer Vision Pipeline
Autonomous Clinical Triage Agent
FastAPI & Redis Inference Engine
Real-Time Telemetry Medical UI