Nai, Y., Cheong, D. L. H., Roy, S., Kok, T., Stephenson, M. C., Schaefferkoetter, J., . . . Reilhac, A. (2023). Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions. Magnetic resonance imaging, 100, 64-72. https://doi.org/10.1016/j.mri.2023.03.009
Citace podle Chicago (17th ed.)Nai, Ying-Hwey, et al. "Comparison of Quantitative Parameters and Radiomic Features as Inputs into Machine Learning Models to Predict the Gleason Score of Prostate Cancer Lesions." Magnetic Resonance Imaging 100 (2023): 64-72. https://doi.org/10.1016/j.mri.2023.03.009.
Citace podle MLA (9th ed.)Nai, Ying-Hwey, et al. "Comparison of Quantitative Parameters and Radiomic Features as Inputs into Machine Learning Models to Predict the Gleason Score of Prostate Cancer Lesions." Magnetic Resonance Imaging, vol. 100, 2023, pp. 64-72, https://doi.org/10.1016/j.mri.2023.03.009.