Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study

MLA

Lue, Kun-Han, et al. “Prognostic Value of Combining Clinical Factors, 18F-FDG PET-Based Intensity, Volumetric Features, and Deep Learning Predictor in Patients with EGFR-Mutated Lung Adenocarcinoma Undergoing Targeted Therapies: A Cross-Scanner and Temporal Validation Study.” Annals of Nuclear Medicine, vol. 38, no. 8, Aug. 2024, pp. 647–58. EBSCOhost, https://doi.org/10.1007/s12149-024-01936-2.

APA

Lue, K.-H., Chen, Y.-H., Chu, S.-C., Lin, C.-B., Wang, T.-F., & Liu, S.-H. (2024). Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study. Annals of Nuclear Medicine, 38(8), 647–658. https://doi.org/10.1007/s12149-024-01936-2

Chicago

Lue, Kun-Han, Yu-Hung Chen, Sung-Chao Chu, Chih-Bin Lin, Tso-Fu Wang, and Shu-Hsin Liu. 2024. “Prognostic Value of Combining Clinical Factors, 18F-FDG PET-Based Intensity, Volumetric Features, and Deep Learning Predictor in Patients with EGFR-Mutated Lung Adenocarcinoma Undergoing Targeted Therapies: A Cross-Scanner and Temporal Validation Study.” Annals of Nuclear Medicine 38 (8): 647–58. doi:10.1007/s12149-024-01936-2.