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

• The Sybil model was validated using data from over 21,000 individuals aged 50-80 who underwent LDCT screening between 2009 and 2021.
• Sybil demonstrated strong predictive performance for lung cancer diagnosis both at one and six years following the scan.
• The model was effective even for never-smokers, a group for whom conventional screening guidelines may not apply.
• The research was presented at the ATS 2025 International Conference.
• Continued 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.

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