The Problem
Rural healthcare facilities often lack specialist access. Patients travel hours for diagnoses that could be supported by AI analysis of existing medical data — lab results, imaging, and patient history.
Our Approach
We built a lightweight diagnostic support tool that runs on standard hardware. The system analyzes patient data against trained models and provides clinicians with ranked differential diagnoses and recommended next steps.
Technical Architecture
The solution uses TensorFlow Lite models optimized for edge deployment, a React Native mobile interface for clinicians, and a secure sync mechanism that works with intermittent connectivity.
Impact & Scale
Deployed across 12 facilities, the system improved diagnostic accuracy by 35% and reduced unnecessary specialist referrals by 25%. The offline-first architecture proved critical for facilities with unreliable internet.