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Gómez OV, Herraiz JL, Udías JM, Haug A, Papp L, Cioni D, Neri E. Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [¹⁸F]F-FDG PET/CT Radiomic Features for Metabolic Response Prediction of Metastatic Breast Cancer Lesions. Cancers. 2022; 14(12):2922. https://doi.org/10.3390/cancers14122922

Gómez, Ober Van, Joaquin L. Herraiz, José Manuel Udías, Alexander Haug, Laszlo Papp, Dania Cioni, and Emanuele Neri. 2022. "Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [¹⁸F]F-FDG PET/CT Radiomic Features for Metabolic Response Prediction of Metastatic Breast Cancer Lesions" Cancers 14, no. 12: 2922. https://doi.org/10.3390/cancers14122922

Gómez, O. V., Herraiz, J. L., Udías, J. M., Haug, A., Papp, L., Cioni, D., & Neri, E. (2022). Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [¹⁸F]F-FDG PET/CT Radiomic Features for Metabolic Response Prediction of Metastatic Breast Cancer Lesions. Cancers, 14(12), 2922. https://doi.org/10.3390/cancers14122922