Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.

Autor: Ferreras A; Department of Signal Theory and Communications and Telematics Engineering, University of Valladolid, Paseo de Belén 15, Valladolid, 47011, Spain., Sumalla-Cano S; Research Group on Foods, Nutritional Biochemistry and Health, European University of the Atlantic, Santander, 39011, Spain.; Department of Health, Nutrition and Sport, Iberoamerican International University, Campeche, 24560, Mexico., Martínez-Licort R; Telemedicine and eHealth Research Group, Department of Signal Theory and Communications and Telematics Engineering, University of Valladolid, Paseo de Belén 15, Valladolid, 47011, Spain. rosmerimartliot@gmail.com.; Department of Telecommunications, University of Pinar del Río, Pinar del Río, Cuba. rosmerimartliot@gmail.com., Elío I; Research Group on Foods, Nutritional Biochemistry and Health, European University of the Atlantic, Santander, 39011, Spain.; Department of Health, Nutrition and Sport, Iberoamerican International University, Campeche, 24560, Mexico., Tutusaus K; Higher Polytechnic School, European University of the Atlantic, Santander, 39011, Spain.; Higher Polytechnic School, Iberoamerican International University, Campeche, 24560, Mexico., Prola T; Faculty of Social Sciences and Humanites, European University of the Atlantic, Santander, Spain., Vidal-Mazón JL; Higher Polytechnic School, European University of the Atlantic, Santander, 39011, Spain.; Higher Polytechnic School, International University of Cuanza, Estrada nacional 250, Cuito-Bié, Angola.; Higher Polytechnic School, Iberoamerican International University, Arecibo, 00613, Puerto Rico., Sahelices B; Research group GCME, Department of Computer Science, University of Valladolid, Paseo de Belén 15, Valladolid, 47011, Spain., de la Torre Díez I; Department of Signal Theory and Communications and Telematics Engineering, University of Valladolid, Paseo de Belén 15, Valladolid, 47011, Spain.
Jazyk: angličtina
Zdroj: Journal of medical systems [J Med Syst] 2023 Jan 13; Vol. 47 (1), pp. 8. Date of Electronic Publication: 2023 Jan 13.
DOI: 10.1007/s10916-022-01904-1
Abstrakt: Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics.
(© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze: MEDLINE
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