AI-Powered Healthcare Platform: 40% Improvement in Diagnostic Accuracy
HIPAA-compliant AI platform processing 50K+ medical images monthly with industry-leading accuracy.
The Challenge
Understanding the Problem
Radiologists were overwhelmed with 1000+ images/day across multiple hospitals. This led to burnout, occasional missed diagnoses, and inefficient resource allocation. The client needed AI-assisted diagnosis while maintaining strict HIPAA compliance.
Our Approach
Structured Methodology
- Built custom ML model trained on 2M+ labeled medical images
- Implemented secure FTP/SFTP for encrypted medical image transfer
- Created audit logging for every model inference (SOC 2 compliance)
- Integrated with major EMR systems (Epic, Cerner) using HL7 standards
- Deployed on dedicated on-premise servers (no cloud data movement)
The Solution
What We Built
Developed an ML pipeline that pre-screens chest X-rays and flags potential abnormalities. Radiologists review AI-highlighted regions, reducing review time by 40%. The system achieves 98% sensitivity and integrates seamlessly with hospital workflows.
Architecture Diagram
Available upon request
Results
Measurable Impact
98%
diagnostic accuracy
50K+
images/month
40%
efficiency gain
Technology Stack
Project Timeline
9 months from kickoff to production launch
"The AI system has revolutionized our diagnostic workflow. Our radiologists are more efficient, and patient outcomes have improved significantly."
Dr. Michael Rodriguez
Metropolitan Healthcare Group
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