Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study

MLA

Ying Zeng, et al. “Radiomics Integration Based on Intratumoral and Peritumoral Computed Tomography Improves the Diagnostic Efficiency of Invasiveness in Patients with Pure Ground-Glass Nodules: A Machine Learning, Cross-Sectional, Bicentric Study.” Journal of Cardiothoracic Surgery, vol. 20, no. 1, Feb. 2025, pp. 1–9. EBSCOhost, https://doi.org/10.1186/s13019-024-03289-3.

APA

Ying Zeng, Jing Chen, Shanyue Lin, Haibo Liu, Yingjun Zhou, & Xiao Zhou. (2025). Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study. Journal of Cardiothoracic Surgery, 20(1), 1–9. https://doi.org/10.1186/s13019-024-03289-3

Chicago

Ying Zeng, Jing Chen, Shanyue Lin, Haibo Liu, Yingjun Zhou, and Xiao Zhou. 2025. “Radiomics Integration Based on Intratumoral and Peritumoral Computed Tomography Improves the Diagnostic Efficiency of Invasiveness in Patients with Pure Ground-Glass Nodules: A Machine Learning, Cross-Sectional, Bicentric Study.” Journal of Cardiothoracic Surgery 20 (1): 1–9. doi:10.1186/s13019-024-03289-3.