Back to all news

AI Model 'Sybil' Predicts Lung Cancer Risk from Single LDCT Scan

EurekAlertResearch
AI Model 'Sybil' Predicts Lung Cancer Risk from Single LDCT Scan

A deep learning model named Sybil can predict future lung cancer risk from a single low-dose chest CT scan, as validated in a large Asian cohort.

Key Details

  • 1The Sybil model was validated using data from over 21,000 individuals aged 50-80 who underwent LDCT screening between 2009 and 2021.
  • 2Sybil demonstrated strong predictive performance for lung cancer diagnosis both at one and six years following the scan.
  • 3The model was effective even for never-smokers, a group for whom conventional screening guidelines may not apply.
  • 4The research was presented at the ATS 2025 International Conference.
  • 5Continued prospective validation is planned to assess clinical use and prediction of lung cancer-specific mortality.

Why It Matters

This advancement could help tailor lung cancer screening strategies, especially benefiting populations (such as Asian never-smokers) not well-served by current guidelines. A validated AI risk tool from a single scan could make screening more efficient and personalized in routine radiological practice.

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.