Healthcare Diagnostic AI
Overview
A hospital network needed to reduce the backlog of radiology reads without compromising accuracy. We built a computer vision pipeline that pre-screens chest X-rays, flags anomalies, and prioritizes the radiologist queue.
The Challenge
Radiologists were overwhelmed with volume, leading to 48-hour read times. The client needed AI assistance without replacing clinical judgment.
Our Solution
We trained a ResNet-based classifier on 200k labeled X-rays, built a HIPAA-compliant API, and integrated it into the existing PACS workflow as a second-reader tool.
Tech Stack
Client
Regional Hospital Network
Duration
18 weeks
Key Outcomes
60% reduction in average read time
99.2% diagnostic accuracy on test set
HIPAA-compliant deployment
Radiologist satisfaction score: 4.8/5
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