Machine learning, applied to complex multidimensional data, is shown to provide personalized dietary recommendations to control blood glucose levels. This is a step towards integrating the gut microbiome into personalized medicine.
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References
Bauer, P., Thorpe, A. & Brunet, G. Nature 525, 47–55 (2015).
Zeevi, D. et al. Cell 163, 1079–1094 (2015).
Chen, L., Magliano, D. J. & Zimmet, P. Z. Nature Rev. Endocrinol. 8, 228–236 (2012).
Ludwig, D. S. J. Am. Med. Assoc. 287, 2414–2423 (2002).
Willett, W., Manson, J. & Liu, S. Am. J. Clin. Nutr. 76, 274S–280S (2002).
Wu, H., Tremaroli, V. & Bäckhed, F. Trends Endocrinol. Metab. 26, 758–770 (2015).
Hsiao, E. Y. et al. Cell 155, 1451–1463 (2013).
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Sonnenburg, E., Sonnenburg, J. A personal forecast. Nature 528, 484–486 (2015). https://doi.org/10.1038/528484a
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DOI: https://doi.org/10.1038/528484a
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