Improving the prediction of Spreading Through Air Spaces (STAS) in primary lung cancer with a dynamic dual-delta hybrid machine learning model: a multicenter cohort study

• Main Authors: Weiqiu Jin (Author), Leilei Shen (Author), Yu Tian (Author), Hongda Zhu (Author), Ningyuan Zou (Author), Mengwei Zhang (Author), Qian Chen (Author), Changzi Dong (Author), Qisheng Yang (Author), Long Jiang (Author), Jia Huang (Author), Zheng Yuan (Author), Xiaodan Ye (Author), Qingquan Luo (Author)
• Format: Book
• Published: BMC, 2023-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Background Reliable pre-surgical prediction of spreading through air spaces (STAS) in primary lung cancer is essential for precision treatment and surgical decision-making. We aimed to develop and validate a dual-delta deep-learning and radiomics model based on pretreatment computed tomogra...