APA (7th ed.) Citation

Frood, R., Clark, M., Burton, C., Tsoumpas, C., Frangi, A. F., Gleeson, F., . . . Scarsbrook, A. (2022). Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma. European Radiology, 32(10), 7237. https://doi.org/10.1007/s00330-022-09039-0

Chicago Style (17th ed.) Citation

Frood, Russell, Matt Clark, Cathy Burton, Charalampos Tsoumpas, Alejandro F. Frangi, Fergus Gleeson, Chirag Patel, and Andrew Scarsbrook. "Utility of Pre-treatment FDG PET/CT-derived Machine Learning Models for Outcome Prediction in Classical Hodgkin Lymphoma." European Radiology 32, no. 10 (2022): 7237. https://doi.org/10.1007/s00330-022-09039-0.

MLA (9th ed.) Citation

Frood, Russell, et al. "Utility of Pre-treatment FDG PET/CT-derived Machine Learning Models for Outcome Prediction in Classical Hodgkin Lymphoma." European Radiology, vol. 32, no. 10, 2022, p. 7237, https://doi.org/10.1007/s00330-022-09039-0.