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.
Source
EurekAlert
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