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Dietary intake is considered one of the major research issues in the field of nutrition and health care. However, existing tools are time consuming and require skilled people to interview patients and collect useful data. In this paper, we start by determining the nutritional needs of patients and then we propose a method for personalizing meals using artificial intelligence (AI) methods. The basic idea is to use images of food before and after consumption and to estimate nutrient intakes using image analysis methods. These methods are rapidly evolving with applicable solutions in the nutrition field towards the use of machine learning algorithms. Finally, the design and architecture of our prototype are detailed and evaluated in order to enhance the system functionalities.
Azzimani et al. (Thu,) studied this question.