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

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 tomography (CT)...

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Detalles Bibliográficos
Autores principales: Jin, Weiqiu, Shen, Leilei, Tian, Yu, Zhu, Hongda, Zou, Ningyuan, Zhang, Mengwei, Chen, Qian, Dong, Changzi, Yang, Qisheng, Jiang, Long, Huang, Jia, Yuan, Zheng, Ye, Xiaodan, Luo, Qingquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668492/
https://www.ncbi.nlm.nih.gov/pubmed/37996894
http://dx.doi.org/10.1186/s40364-023-00539-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668492/
https://www.ncbi.nlm.nih.gov/pubmed/37996894
http://dx.doi.org/10.1186/s40364-023-00539-9

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