Ankenbrand, M. J., Shainberg, L., Hock, M., Lohr, D., & Schreiber, L. M. (2021). Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI. BMC Medical Imaging, 21(1), 1-8. https://doi.org/10.1186/s12880-021-00551-1
ISO-690 (author-date, English)ANKENBRAND, Markus J., SHAINBERG, Liliia, HOCK, Michael, LOHR, David und SCHREIBER, Laura M., 2021. Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI. BMC Medical Imaging. 15 Februar 2021. Vol. 21, no. 1, p. 1-8. DOI 10.1186/s12880-021-00551-1.
Modern Language Association 9th editionAnkenbrand, M. J., L. Shainberg, M. Hock, D. Lohr, und L. M. Schreiber. „Sensitivity Analysis for Interpretation of Machine Learning Based Segmentation Models in Cardiac MRI.“. BMC Medical Imaging, Bd. 21, Nr. 1, Februar 2021, S. 1-8, https://doi.org/10.1186/s12880-021-00551-1.
Mohr Siebeck - Recht (Deutsch - Österreich)Ankenbrand, Markus J./Shainberg, Liliia/Hock, Michael/Lohr, David/Schreiber, Laura M.: Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI., BMC Medical Imaging 2021, 1-8.
Emerald - HarvardAnkenbrand, M.J., Shainberg, L., Hock, M., Lohr, D. und Schreiber, L.M. (2021), „Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI.“, BMC Medical Imaging, Vol. 21 No. 1, S. 1-8.