Case Study Image

Transforming radiology with AI-powered diagnostics

Client:

Trinity Global Medical Center (Germany)

Type:

Multispecialty Teaching Hospital

Annual imaging volume:

500,000+ scans

Challenge:

Delays in radiology reporting, diagnostic inconsistencies, radiologist burnout

Trinity Global Medical Center, a leading multispecialty hospital in Germany, faced mounting pressure from increasing scan volumes, delayed report turnaround times, and radiologist burnout. By implementing our AI-Powered Diagnostics Platform, the hospital transformed its radiology department—cutting report delivery times by more than half, improving detection accuracy by 9%, and enabling faster, life-saving interventions.

Recognizing the urgent need for faster, more accurate diagnostics, the hospital partnered with us to deploy our AI-Powered Diagnostics Platform.

This cloud-based solution integrates directly with their existing PACS and EHR systems, analyzing imaging data in real-time, flagging urgent cases for immediate attention, and generating structured reports with high-confidence findings.

Overview Image
Challenges

With increasing scan volumes and limited radiology staff, Trinity Global faced:

  • Delayed report turnaround (up to 48 hours)
  • High dependency on manual reads
  • Variation in interpretation across radiologists
  • Risk of missed early-stage findings
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Solutions

The solution was designed to work alongside radiologists, not replace them—providing real-time insights, prioritizing urgent cases, and standardizing reporting.

  • Real-Time Imaging Analysis
    CT, MRI, and X-rays processed instantly with AI-powered anomaly detection.
  • Critical Case Alerts
    Automatic flagging of life-threatening findings such as hemorrhages, pulmonary embolisms, and fractures.
  • Confidence Scoring
    AI assigns probability ratings to its findings, helping radiologists prioritize review.
  • Workflow Integration
    Direct integration with PACS and hospital EHR for seamless adoption.
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Outcome
  • Enabled real-time triaging in emergency cases
  • Improved diagnostic confidence among clinicians
  • Reduced radiologist burnout through smart workflows
  • Contributed to early cancer detection in 17 new cases
Results

Highlight measurable improvements and business impact, with data.

Under 6 hours

Report Turnaround Time

85% average

Detection Accuracy

30 reports/day

Radiologist Productivity
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Dr. Laura Kim

Radiologist

AI doesn’t replace clinical judgment—it enhances it. With its precision, we’re catching early signs of diseases that were once easy to overlook.

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