Figure 2:

Examples of Sybil, an open-source deep learning model, correctly predicting lung cancers (future lung cancer). (A, B) Axial low-dose CT image of the lungs in a 55-year-old heavy-smoking man shows no abnormality, but the attention map of Sybil focused on the right upper lobe (arrow). The Sybil lung risk scores were 1.1% for 1-year risk, 2.4% for 2-year risk, 4.2% for 3-year risk, 5.6% for 4-year risk, 6.8% for 5-year risk, and 10.5% for 6-year risk. (C) Axial CT image after 5 years shows that the patient had a 7.3-cm mass in the right upper lobe, diagnosed as lung cancer (arrow; adenocarcinoma). The Sybil lung risk score is a deep learning–based risk score for predicting future lung cancer risk within 6 years from a low-dose chest CT scan.