File:Fig2 Berciano FrontNutr2022 9.jpg
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Summary
| Description |
Fig. 2 Deep phenotyping and multiomic integration in precision nutrition. Multiple data layers that make up an individual deep phenotyping profile are integrated and analyzed using a neural network approach to provide optimized dietary recommendations, leading to behavior change and improved health outcomes. |
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| Source |
Berciano, S.; Figueiredo, J.; Brisbois, T.D.; Alford, S.; Koecher, K.; Eckhouse, S.; Ciati, R.; Kussmann, M.; Ordovas, J.M.; Stebbins, K.; Blumberg, J.B. (2022). "Precision nutrition: Maintaining scientific integrity while realizing market potential". Frontiers in Nutrition 9: 979665. doi:10.3389/fnut.2022.979665. |
| Date |
2022 |
| Author |
Berciano, S.; Figueiredo, J.; Brisbois, T.D.; Alford, S.; Koecher, K.; Eckhouse, S.; Ciati, R.; Kussmann, M.; Ordovas, J.M.; Stebbins, K.; Blumberg, J.B. |
| Permission (Reusing this file) |
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Licensing
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This work is licensed under the Creative Commons Attribution 4.0 License. |
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| current | 18:49, 16 December 2022 | | 1,021 × 562 (309 KB) | Shawndouglas (talk | contribs) |
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