Predicting Plasma Vitamin C Using Machine Learning

References

• Archer, E., G. Pavela, and C. J. Lavie. 2015. The inadmissibility of what we eat in america and NHANES dietary data in nutrition and obesity research and the scientific formulation of national dietary guidelines. Mayo Clinic Proceedings 90 (7):911-926. doi:10.1016/j.mayocp.2015.04.009
   Google Scholar
• Awad, M., R. Khanna, M. Awad, and R. Khanna. 2015. Support Vector Regression. In Efficient Learning Machines, Jeffrey Pepper; Steve Weiss; Patrick Hauke, edited by, 67-81. New York, US: Apress. doi: 10.1007/978-1-4302-5990-9_4.
   Google Scholar
• Baek, J. W., J. C. Kim, J. Chun, and K. Chung. 2019. Hybrid clustering based health decision-making for improving dietary habits. Technology and Health Care 27 (5):459–2481. doi:10.3233/THC-191730.
   PubMed Web of Science ®Google Scholar
• Berry, S. E., A. M. Valdes, D. A. Drew, F. Asnicar, M. Mazidi, J. Wolf, J. Capdevila, G. Hadjigeorgiou, R. Davies, H. Al Khatib, et al. 2020. Human postprandial responses to food and potential for precision nutrition. Nature Medicine 26 (6):964–73. doi:10.1038/s41591-020-0934-0.
   PubMed Web of Science ®Google Scholar
• Breiman, L. 2001. Random forests. Machine Learning 45 (1):5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Bzdok, D., N. Altman, and M. Krzywinski. 2018. Points of significance: statistics versus machine learning. Nature Methods 15 (4):233–34. doi:10.1038/NMETH.4642.
   PubMed Web of Science ®Google Scholar
• Carr, A. C., and S. Rowe. 2020. Factors affecting vitamin c status and prevalence of deficiency: A global health perspective. Nutrients 12(7): 1963. Switzerland. MDPI AG. doi:10.3390/nu12071963.
   Google Scholar
• Cecil, J. E., and K. L. Barton. 2020. Inter-individual differences in the nutrition response: From research to recommendations. Proceedings of the Nutrition Society 79 (2):171–73. doi:10.1017/S0029665119001198.
   PubMed Web of Science ®Google Scholar
• Celis-Morales, C., K. M. Livingstone, C. F. M. Marsaux, A. L. Macready, R. Fallaize, C. B. O’Donovan, C. Woolhead, H. Forster, M. C. Walsh, S. Navas-Carretero, et al. 2017. Effect of personalized nutrition on health-related behaviour change: Evidence from the Food4Me European randomized controlled trial. International Journal of Epidemiology 46 (2):578–88. doi:10.1093/IJE/DYW186.
   PubMed Web of Science ®Google Scholar
• Chen, T., and C. Guestrin 2016. XGBoost: A scalable tree boosting system. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, California. doi:10.1145/2939672.2939785
   Google Scholar
• de Toro-martín, J., B. J. Arsenault, J. P. Després, and M. C. Vohl. 2017. Precision nutrition: A review of personalized nutritional approaches for the prevention and management of metabolic syndrome. In Nutrients, vol. 9 (8): 913. Switzerland: MDPI AG. doi:10.3390/nu9080913.
   Google Scholar
• Dehghan, M., N. Akhtar-Danesh, C. R. McMillan, and L. Thabane. 2007. Is plasma vitamin C an appropriate biomarker of vitamin C intake? A systematic review and meta-analysis. Nutrition Journal 6. doi:10.1186/1475-2891-6-41.
   Web of Science ®Google Scholar
• Hagel, A. F., H. Albrecht, W. Dauth, W. Hagel, F. Vitali, I. Ganzleben, H. W. Schultis, P. C. Konturek, J. Stein, M. F. Neurath, et al. 2018. Plasma concentrations of ascorbic acid in a cross section of the German population. Journal of International Medical Research 46 (1):168–74. doi:10.1177/0300060517714387.
   PubMed Web of Science ®Google Scholar
• Huang, Z. 1998. Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Mining and Knowledge Discovery 2 (3):283–304. doi:10.1023/A:1009769707641.
   Web of Science ®Google Scholar
• Jollife, I. T., and J. Cadima. 2016. Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374:20150202. doi:10.1098/rsta.2015.0202.
   PubMed Web of Science ®Google Scholar
• Jungert, A., and M. Neuhäuser-Berthold. 2015. The lower vitamin C plasma concentrations in elderly men compared with elderly women can partly be attributed to a volumetric dilution effect due to differences in fat-free mass. British Journal of Nutrition 113:859–64. doi:10.1017/S0007114515000240.
   PubMed Web of Science ®Google Scholar
• Juraschek, S. P., E. Guallar, L. J. Appel, and E. R. Miller. 2012. Effects of vitamin c supplementation on blood pressure: A meta-analysis of randomized controlled trials. American Journal of Clinical Nutrition 95 (5):1079–88. doi:10.3945/ajcn.111.027995.
   PubMed Web of Science ®Google Scholar
• Kanungo, T., D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu. 2002. An efficient k-means clustering algorithms: Analysis and implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (7):881-892. doi:10.1109/TPAMI.2002.1017616
   Google Scholar
• Kim, J. C., and K. Chung. 2020. Knowledge-based hybrid decision model using neural network for nutrition management. Information Technology and Management 21 (1):29–39. doi:10.1007/s10799-019-00300-5.
   Web of Science ®Google Scholar
• Kirk, D., C. Catal, and B. Tekinerdogan. 2021. Precision nutrition: A systematic literature review. Computers in Biology and Medicine 133. doi:10.1016/J.COMPBIOMED.2021.104365.
   Web of Science ®Google Scholar
• Kraemer, C. M. 2020. Vitamin C (Ascorbic Acid): Reference Range, Interpretation, Collection and Panels. Reference Range, Interpretation, Collection and Panels. Retrieved from https://emedicine.medscape.com/article/2088649-overview (Accessed on 20 June 2021).
   Google Scholar
• Mannor, S., X. Jin, J. Han, X. Jin, J. Han, X. Jin, J. Han, and X. Zhang. 2011. K-Means Clustering. In Encyclopedia of Machine Learning, 563–64. US: Springer. doi:10.1007/978-0-387-30164-8_425.
   Google Scholar
• McDonald, G. C. 2009. Ridge regression. Wiley Interdisciplinary Reviews. Computational Statistics 1 (1):93–100. doi:10.1002/wics.14.
   Google Scholar
• Myint, P. K., R. N. Luben, N. J. Wareham, and K. T. Khaw. 2011. Association between plasma vitamin C concentrations and blood pressure in the European prospective investigation into cancer-Norfolk population-based study. Hypertension (3):372–79. doi:10.1161/HYPERTENSIONAHA.111.171108.
   PubMed Web of Science ®Google Scholar
• Ness, A. R., D. Chee, and P. Elliott. 1997. Vitamin C and blood pressure - an overview. Journal of Human Hypertension 11 (6):343–50. doi:10.1038/sj.jhh.1000423.
   PubMed Web of Science ®Google Scholar
• NHANES. 2015. Measuring guides for the dietary recall interview. accessed 2020. https://www.cdc.gov/nchs/nhanes/measuring_guides_dri/measuringguides.htm
   Google Scholar
• NHANES. 2017. About the national health and nutrition examination survey. accessed 2020. https://www.cdc.gov/nchs/nhanes/about_nhanes.htm
   Google Scholar
• NIH. 2020. Vitamin C - fact sheet for health professionals. accessed https://ods.od.nih.gov/factsheets/VitaminC-HealthProfessional/#:%7E:text=Vitamin%20C%20is%20required%20for,vital%20role%20in%20wound%20healing
   Google Scholar
• Olive, D. J. 2017. Linear regression. Linear Regression. doi:10.1007/978-3-319-55252-1.
   Google Scholar
• Ordovas, J. M., L. R. Ferguson, E. S. Tai, and J. C. Mathers. 2018. Personalised nutrition and health. British Medical Journal 361. doi:10.1136/bmj.k2173.
   Google Scholar
• Ramyaa, R., O. Hosseini, G. P. Krishnan, and S. Krishnan. 2019. Phenotyping women based on dietary macronutrients, physical activity, and body weight using machine learning tools. Nutrients 11 (7):1681. doi:10.3390/nu11071681.
   PubMed Web of Science ®Google Scholar
• Rowe, M. 2019. An Introduction to Machine Learning for Clinicians. Academic Medicine 94 (10):1433–36. doi:10.1097/ACM.0000000000002792.
   PubMed Web of Science ®Google Scholar
• Shiao, S. P. K., J. Grayson, A. Lie, and C. H. Yu. 2018. Personalized nutrition—genes, diet, and related interactive parameters as predictors of cancer in multiethnic colorectal cancer families. Nutrients 10 (6):795. doi:10.3390/nu10060795.
   PubMed Web of Science ®Google Scholar
• Tibshirani, R. 1996. Regression Shrinkage and Selection Via the Lasso. Journal of the Royal Statistical Society: Series B (Methodological). doi:10.1111/j.2517-6161.1996.tb02080.x.
   Web of Science ®Google Scholar
• Travica, N., K. Ried, A. Sali, I. Hudson, A. Scholey, and A. Pipingas. 2019. Plasma Vitamin C concentrations and cognitive function: A cross-sectional study. Frontiers in Aging Neuroscience 11. doi:10.3389/fnagi.2019.00072.
   PubMed Web of Science ®Google Scholar
• Zeevi, D., T. Korem, N. Zmora, D. Israeli, D. Rothschild, A. Weinberger, O. Ben-Yacov, D. Lador, T. Avnit-Sagi, M. Lotan-Pompan, et al. 2015. Personalized Nutrition by Prediction of Glycemic Responses. Cell 163 (5):1079–94. doi:10.1016/j.cell.2015.11.001.
   PubMed Web of Science ®Google Scholar