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WCLC 2026 | Sybil implementation and social determinants of lung cancer risk prediction
Evan Garrad, MD, University of Illinois Chicago, Chicago, IL, discusses the implementation of the Sybil, an open access machine learning model that assesses lung cancer risk from low-dose CT scans, and presents exploratory analysis on the associations between patient and neighborhood characteristics and Sybil scores in a diverse, high-risk patient population. The analysis revealed several associations with social determinants of health, which are hypothesis-generating for future research. This interview took place at the IASLC 2026 World Conference on Lung Cancer congress in Seoul, Republic of Korea.
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