Back to all news

Generative AI Tool Boosts Workflow in Chest X-Ray Interpretation

AuntMinnieIndustry

A large radiology practice found a generative AI model beneficial for chest x-ray worklist prioritization and quality assurance.

Key Details

  • 1The AI model generated text-based clinical reports for 34,680 chest x-ray studies over two weeks.
  • 2An NLP model mapped reports to 155 chest x-ray findings, comparing AI and radiologist results.
  • 3Sensitivity and specificity for pneumothorax detection were 62.4% and 99.3%, respectively.
  • 4Studies with positive pneumothorax findings were flagged for urgent review; 36 cases with discrepant findings went to secondary review.
  • 525% of secondary-reviewed cases revealed missed pneumothorax by radiologists.
  • 644% of radiologists rated AI-generated reports as equivalent in quality to their own.

Why It Matters

This demonstrates tangible workflow improvements and diagnostic support from generative AI in radiology, suggesting the potential to reduce radiologist workload and aid in addressing staffing shortages.

Ready to Sharpen Your Edge?

Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.