Predictive Efficacy of a Radiomics Random Forest Model for Identifying Pathological Subtypes of Lung Adenocarcinoma Presenting as Ground-Glass Nodules

MLA

Fen-hua Zhao, et al. “Predictive Efficacy of a Radiomics Random Forest Model for Identifying Pathological Subtypes of Lung Adenocarcinoma Presenting as Ground-Glass Nodules.” Frontiers in Oncology, vol. 12, May 2022. EBSCOhost, https://doi.org/10.3389/fonc.2022.872503.

APA

Fen-hua Zhao, Hong-jie Fan, Kang-fei Shan, Long Zhou, Zhen-zhu Pang, Chun-long Fu, Ze-bin Yang, Mei-kang Wu, Ji-hong Sun, Xiao-ming Yang, & Zhao-hui Huang. (2022). Predictive Efficacy of a Radiomics Random Forest Model for Identifying Pathological Subtypes of Lung Adenocarcinoma Presenting as Ground-Glass Nodules. Frontiers in Oncology, 12. https://doi.org/10.3389/fonc.2022.872503

Chicago

Fen-hua Zhao, Hong-jie Fan, Kang-fei Shan, Long Zhou, Zhen-zhu Pang, Chun-long Fu, Ze-bin Yang, et al. 2022. “Predictive Efficacy of a Radiomics Random Forest Model for Identifying Pathological Subtypes of Lung Adenocarcinoma Presenting as Ground-Glass Nodules.” Frontiers in Oncology 12 (May). doi:10.3389/fonc.2022.872503.