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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 |
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| Authors: | Alessio Ragno Anna Baldisserotto Lorenzo Antonini Manuela Sabatino Filippo Sapienza Erika Baldini Raissa Buzzi Silvia Vertuani Stefano Manfredini |
| Institution: | 1.Department of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University, 00185 Rome, Italy;2.Department of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy; (A.B.); (E.B.); (R.B.);3.Department of Drug Chemistry and Technology, Sapienza University, 00185 Rome, Italy; (L.A.); (M.S.); (F.S.);4.Master Course in Cosmetic Sciences, Department of Life Sciences and Biotechnology, University of Ferrara, 44100 Ferrara, Italy |
| Abstract: | |
| Keywords: | QCAR machine learning deep learning essential oils pharmaceutics nutraceutics cosmeceutics |