Kebir, S.; Schmidt, T.; Weber, M.; Lazaridis, L.; Galldiks, N.; Langen, K.-J.; Kleinschnitz, C.; Hattingen, E.; Herrlinger, U.; Lohmann, P.;
et al. A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma. Cancers 2020, 12, 3080.
https://doi.org/10.3390/cancers12113080
AMA Style
Kebir S, Schmidt T, Weber M, Lazaridis L, Galldiks N, Langen K-J, Kleinschnitz C, Hattingen E, Herrlinger U, Lohmann P,
et al. A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma. Cancers. 2020; 12(11):3080.
https://doi.org/10.3390/cancers12113080
Chicago/Turabian Style
Kebir, Sied, Teresa Schmidt, Matthias Weber, Lazaros Lazaridis, Norbert Galldiks, Karl-Josef Langen, Christoph Kleinschnitz, Elke Hattingen, Ulrich Herrlinger, Philipp Lohmann,
and et al. 2020. "A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma" Cancers 12, no. 11: 3080.
https://doi.org/10.3390/cancers12113080
APA Style
Kebir, S., Schmidt, T., Weber, M., Lazaridis, L., Galldiks, N., Langen, K.-J., Kleinschnitz, C., Hattingen, E., Herrlinger, U., Lohmann, P., & Glas, M.
(2020). A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma. Cancers, 12(11), 3080.
https://doi.org/10.3390/cancers12113080
