American Psychological Association 6th edition

Kebir, S., Schmidt, T. M., Weber, M., Lazaridis, L., Galldiks, N., Langen, K.-J., Kleinschnitz, C., Hattingen, E., Herrlinger, U., Lohmann, P., & Glas, M. (o. J.). 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 [Electronic]. Cancers, (Band 11 (2020), Artikel-ID: 3080), , Artikel-ID: 3080. https://doi.org/10.3390/cancers12113080

ISO-690 (author-date, English)

KEBIR, Sied, SCHMIDT, Teresa Maria, WEBER, Matthias, LAZARIDIS, Lazaros, GALLDIKS, Norbert, LANGEN, Karl-Josef, KLEINSCHNITZ, Christoph, HATTINGEN, Elke, HERRLINGER, Ulrich, LOHMANN, Philipp und GLAS, Martin, [no date]. 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. No. Band 11 (2020), Artikel-ID: 3080, p. , Artikel-ID: 3080. DOI 10.3390/cancers12113080.

Modern Language Association 9th edition

Kebir, S., T. M. Schmidt, M. Weber, L. Lazaridis, N. Galldiks, K.-J. Langen, C. Kleinschnitz, E. Hattingen, U. Herrlinger, P. Lohmann, und M. Glas. „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, electronic, Nr. Band 11 (2020), Artikel-ID: 3080, Universitätsbibliothek Johann Christian Senckenberg Basel : MDPI, 2009-, S. , Artikel-ID: 3080, https://doi.org/10.3390/cancers12113080.

Mohr Siebeck - Recht (Deutsch - Österreich)

Kebir, Sied/Schmidt, Teresa Maria/Weber, Matthias/Lazaridis, Lazaros/Galldiks, Norbert/Langen, Karl-Josef u. a.: 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 , Artikel-ID: 3080.

Emerald - Harvard

Kebir, S., Schmidt, T.M., Weber, M., Lazaridis, L., Galldiks, N., Langen, K.-J., Kleinschnitz, C., Hattingen, E., Herrlinger, U., Lohmann, P. und Glas, M. (o. J.). „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, Universitätsbibliothek Johann Christian Senckenberg Basel : MDPI, 2009-, Frankfurt am Main, No. Band 11 (2020), Artikel-ID: 3080, S. , Artikel-ID: 3080.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.