PROJECT_002 // MEDICAL IMAGING
MEDISCAN CORE

// OVERVIEW
THE CHALLENGE
Radiologists process hundreds of medical images daily, but human fatigue and diagnostic variability lead to critical errors. Detecting subtle abnormalities in CT scans, MRIs, and X-rays requires years of specialized experience.
Compaiser developed a computer vision system that consistently surpasses board-certified radiologists in diagnostic accuracy, reducing analysis time from 45 minutes to 2.3 seconds.
// SOLUTION
AUTONOMOUS MEDICAL VISION
We trained 3D convolutional neural networks on 4.2 million medical images annotated by experts. The system detects 47 different pathology types: tumors, fractures, hemorrhages, infections, and more.
MediScan Core obtained FDA Class II clearance and is deployed in 23 hospitals, processing over 8,000 imaging studies daily with 96.8% diagnostic sensitivity.
// CLINICAL METRICS
96.8%
SENSITIVITY
2.3s
ANALYSIS TIME
23
HOSPITALS
FDA II
CERTIFICATION
// TECHNICAL STACK
AI ARCHITECTURE
- - Modified 3D ResNet-152
- - Attention mechanisms
- - PyTorch framework
- - Medical transfer learning
INTEGRATION
- - DICOM protocol support
- - HL7 FHIR integration
- - PACS system compatible
- - React dashboard frontend
COMPLIANCE
- - FDA 21 CFR Part 820
- - HIPAA compliant
- - ISO 13485 certified
- - CE Mark approved
READY TO DEPLOY?
Compaiser is accepting applications for the next cohort of autonomous ventures.
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