International Journal of Emerging Trends in Health Sciences

Yazarlar: Asım Sinan Yüksel, Fatma Altinsoy, Serhat Uysal

Konular:-

Anahtar Kelimeler:Artificial intelligence,Machine learning,Predictive analysis,Nutrition quality,Nutrition facts.

Özet: Healthy and conscious eating is one of the most important factors affecting our quality of life from infancy to old age. The food that we consume directly affects our mental health, as well as our physical health. Unhealthy eating consists of excessive sugar, fat and salt consumption, overeating or consuming less healthy nutrition than our body needs to function correctly. As the consumption of unhealthy products increases, the likelihood of consuming healthy nutrients needed by the body decreases. In order to prevent this situation, it has become an important issue to obtain information about the nutritional quality of the food products that we consume. In this study, it is aimed to raise awareness about healthy food consumption and provide guidance for people to consume healthy food products. To this end, we conducted an experimental study to estimate the nutritional quality of food products by applying the most commonly used machine learning algorithms, such as Decision Tree, Multilayer Perceptron, Naive Bayes, Random Forest and K-nearest Neighbours. Our experimental results showed that the nutritional quality of foods can be predicted with an accuracy over 91%.  

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