A HIPAA-compliant computer-vision diagnostics assistant that cut radiology review time by 40% with zero missed-finding regressions after launch.
The Operational Problem
MedCore’s radiologists were spending too much time on first-pass review of routine scans, creating a backlog that delayed diagnosis for genuinely urgent cases. Any AI assistance had to meet strict clinical accuracy and compliance bars.
Our Architectural Approach
We built a computer-vision triage model trained and validated against a clinically-labeled dataset, integrated directly into the radiologists’ existing PACS workflow so no new tools were required, and implemented full audit logging and field-level encryption to meet HIPAA requirements.
Measurable Results & Outcomes
- 40%: Reduction in review time
- 99.2%: Model sensitivity on validation set
- 0: Missed-finding regressions post-launch
- HIPAA: Fully compliant architecture
Technology Stack: Python, PyTorch, FastAPI, AWS, PostgreSQL