Nutritional Management of Metabolic Diseases
In this body of work, we propose and develop mathematical approaches for estimating the nutrient content of foods, with a focus on Phenylalanine (Phe), for the dietary management of metabolic diseases. Our contributions include lemmas that can be used as simple guidelines for sweets as well as numerical optimization techniques. The latter have been implemented as web apps. See Boutin’s blog for more details.
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• J.Kim and M.Boutin, “An Approximate Inverse Recipe Method with Application to Automatic Food Analysis,” IEEE Symposium Series on Computational Intelligence, Orlando, FL, December 9–12, 2014.
An inverse numerical problem solved by numerical optimization.
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• J. Kim and M. Boutin, “A List of Phenylalanine to Protein Ratios for Common Foods,” ECE Technical Reports. Paper 456, 2014, available at http://docs.lib.purdue.edu/ecetr/456.
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This list forms the basis of two of our Phe estimation methods.
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• J. Kim and M. Boutin. "Deriving Nutrition Information Using Mathematical Estimation: The Example of Phenylalanine in Sweets with Gelatin." Journal of the Academy of Nutrition and Dietetics 115.9 (2015): 1384-1386.
Mathematical lemmas that can be used as guideline for eating candy.
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• J. Kim and M. Boutin, “New Multipliers for Estimating the Phenylalanine Content of Foods from the Protein Content,” Journal of Food Composition and Analysis, Vol. 42, pp. 117-119, 2015.
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Debunking the 30-50 rule.
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• J.Kim and M. Boutin,”Estimating the Nutrient Content of Commercial Foods from their Label Using Numerical Optimization,” 1st International Workshop on Multimedia Assisted Dietary Management (MADIMA), Genoa, Italy, September 8, 2015.
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Our first stab at estimating Phe using numerical optimization.
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•J. Kim, A. Talikoti, M. Boutin, “A 3-step process to estimate phenylalanine in commercial foods for PKU management,” IEEE Access, Vol. 6, No. 1, December 2018, pp. 30758-30765.
Our most accurate Phe estimation method so far. Based on numerical optimization.
