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- W3091905336 abstract "Foodomics aims to investigate the effects of food on health by collecting a large amount of data from which the relevant information is extracted using data mining methods. Nevertheless, it can be stated that their use is subordinate to software implemented on certain platforms since a lack of experience is often noted in researchers. The present paper is aimed to provide an overview on the latest research advances describing data analysis process in the untargeted approach using data mining methods when analytical techniques such as NMR, chromatography-MS and 2D chromatography are mainly employed. Moreover, it emphasizes the gaps that still need to be filled in the use of data mining methods. Finally, the terminology employed in this field is also explained and discussed." @default.
- W3091905336 created "2020-10-15" @default.
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- W3091905336 date "2021-02-01" @default.
- W3091905336 modified "2023-10-18" @default.
- W3091905336 title "Data mining/machine learning methods in foodomics" @default.
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- W3091905336 doi "https://doi.org/10.1016/j.cofs.2020.09.008" @default.
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