Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagnostic study

OBJECTIVES: To develop and validate a preoperative CT-based nomogram combined with radiomic and clinical–radiological signatures to distinguish preinvasive lesions from pulmonary invasive lesions. METHODS: This was a retrospective, diagnostic study conducted from August 1, 2018, to May 1, 2020, at t...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Luyu, Lin, Weihuan, Xie, Daipeng, Yu, Yunfang, Cao, Hanbo, Liao, Guoqing, Wu, Shaowei, Yao, Lintong, Wang, Zhaoyu, Wang, Mei, Wang, Siyun, Wang, Guangyi, Zhang, Dongkun, Yao, Su, He, Zifan, Cho, William Chi-Shing, Chen, Duo, Zhang, Zhengjie, Li, Wanshan, Qiao, Guibin, Chan, Lawrence Wing-Chi, Zhou, Haiyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Computed Tomography
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831242/
https://www.ncbi.nlm.nih.gov/pubmed/34654966
http://dx.doi.org/10.1007/s00330-021-08268-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831242/
https://www.ncbi.nlm.nih.gov/pubmed/34654966
http://dx.doi.org/10.1007/s00330-021-08268-z

Ejemplares similares