Novel body fat estimation using machine learning and 3-dimensional optical imaging
Author:
Publisher
Springer Science and Business Media LLC
Subject
Nutrition and Dietetics,Medicine (miscellaneous)
Link
http://www.nature.com/articles/s41430-020-0603-x.pdf
Reference11 articles.
1. Ng BK, Sommer MJ, Wong MC, Pagano I, Nie Y, Fan B et al. Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies. Am J Clin Nutr. 2019. https://doi.org/10.1093/ajcn/nqz218.
2. Tinsley GM, Moore ML, Benavides ML, Dellinger JR, Adamson BT. 3-Dimensional optical scanning for body composition assessment: a 4-component model comparison of four commercially available scanners. Clin Nutr 2020. https://doi.org/10.1016/j.clnu.2020.02.008.
3. Wong MC, Ng BK, Kennedy SF, Hwaung P, Liu EY, Kelly NN, et al. Children and adolescents’ anthropometrics body composition from 3-D optical surface scans. Obesity. 2019;27:1738–49. https://doi.org/10.1002/oby.22637.
4. Heymsfield SB, Bourgeois B, Ng BK, Sommer MJ, Li X, Shepherd JA. Digital anthropometry: a critical review. Eur J Clin Nutr. 2018;72:680–7. https://doi.org/10.1038/s41430-018-0145-7.
5. Tinsley GM, Moore ML, Dellinger JR, Adamson BT, Benavides ML. Digital anthropometry via three-dimensional optical scanning: evaluation of four commercially available systems. Eur J Clin Nutr. 2019. https://doi.org/10.1038/s41430-019-0526-6.
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