Development and Validation of a Risk Stratification Model of Pulmonary Ground-Glass Nodules Based on Complementary Lung-RADS 1.1 and Deep Learning Scores

• Main Authors: Qingcheng Meng (Author), Bing Li (Author), Pengrui Gao (Author), Wentao Liu (Author), Peijin Zhou (Author), Jia Ding (Author), Jiaqi Zhang (Author), Hong Ge (Author)
• Format: Book
• Published: Frontiers Media S.A., 2022-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

PurposeTo assess the value of novel deep learning (DL) scores combined with complementary lung imaging reporting and data system 1.1 (cLung-RADS 1.1) in managing the risk stratification of ground-glass nodules (GGNs) and therefore improving the efficiency of lung cancer (LC) screening in China.Mater...