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A feasibility study to assess Mediterranean Diet adherence using an AI-powered system

A feasibility study to assess Mediterranean Diet adherence using an AI-powered system

A feasibility study to assess Mediterranean Diet adherence using an AI-powered system and weight management is currently being conducted by the University of Alicante in Spain. The objective of this study is to analyze the possibility of developing a tool that would enable people to monitor their eating habits in order to better control their weight.

The study will make use of an AI-powered system that will be used to assess the eating habits of participants. This system will take into account different factors such as the type of food consumed, the portion size, and the frequency of meals. It will then provide participants with a score that will indicate their level of adherence to the Mediterranean Diet.

At the end of the study, the team hopes to have a better understanding of the feasibility of such a system. They also hope to identify any potential challenges that need to be addressed before such a tool can be made available to the public.

A feasibility study to assess Mediterranean Diet adherence using an AI-powered system

The aim of this study is to develop and test a new AI-powered system for the assessment of Mediterranean Diet (MD) adherence. The system will use computer vision and machine learning techniques to analyze images of food intake and generate a dietary score. The study will be conducted over a three-month period with a sample of 50 participants. All participants will be asked to take photos of their meals and snacks using a smartphone app. The app will then send the images to a central server where they will be processed by the AI-powered system. The system will generate a dietary score for each participant, which will be used to assess MD adherence. The study will also collect data on participants’ sociodemographic characteristics, dietary habits, and health status. The data will be analyzed to determine the feasibility of using the AI-powered system for the assessment of MD adherence.

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