APA (7th ed.) Citation

AJ, V., V, G., BK, S., L, W., SK, S., JP, R., . . . HMT, T. (2023). Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization. Physics and imaging in radiation oncology, 26, 100450. https://doi.org/10.1016/j.phro.2023.100450

Chicago Style (17th ed.) Citation

AJ, Varghese, et al. "Multi-centre Radiomics for Prediction of Recurrence Following Radical Radiotherapy for Head and Neck Cancers: Consequences of Feature Selection, Machine Learning Classifiers and Batch-effect Harmonization." Physics and Imaging in Radiation Oncology 26 (2023): 100450. https://doi.org/10.1016/j.phro.2023.100450.

MLA (9th ed.) Citation

AJ, Varghese, et al. "Multi-centre Radiomics for Prediction of Recurrence Following Radical Radiotherapy for Head and Neck Cancers: Consequences of Feature Selection, Machine Learning Classifiers and Batch-effect Harmonization." Physics and Imaging in Radiation Oncology, vol. 26, 2023, p. 100450, https://doi.org/10.1016/j.phro.2023.100450.