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Ragno A, Baldisserotto A, Antonini L, Sabatino M, Sapienza F, Baldini E, Buzzi R, Vertuani S, Manfredini S. Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition–Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils. Molecules. 2021; 26(20):6279. https://doi.org/10.3390/molecules26206279

Ragno, Alessio, Anna Baldisserotto, Lorenzo Antonini, Manuela Sabatino, Filippo Sapienza, Erika Baldini, Raissa Buzzi, Silvia Vertuani, and Stefano Manfredini. 2021. "Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition–Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils" Molecules 26, no. 20: 6279. https://doi.org/10.3390/molecules26206279

Ragno, A., Baldisserotto, A., Antonini, L., Sabatino, M., Sapienza, F., Baldini, E., Buzzi, R., Vertuani, S., & Manfredini, S. (2021). Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition–Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils. Molecules, 26(20), 6279. https://doi.org/10.3390/molecules26206279