Can ChatGPT provide appropriate meal plans for NCD patients?

Dietary habits significantly affect health conditions and are closely related to the onset and progression of non-communicable diseases (NCDs). Consequently, a well-balanced diet plays an important role in lessening the effects of various disorders, including NCDs. Several artificial intelligence recommendation systems have been developed to propose healthy and nutritious diets. Most of these systems use expert knowledge and guidelines to provide tailored diets and encourage healthier eating habits. However, new advances in large language models such as ChatGPT, with their ability to produce human-like responses, have led individuals to search for advice in several tasks, including diet recommendations. This study aimed to determine the ability of ChatGPT models to generate appropriate personalized meal plans for patients with obesity, cardiovascular diseases, and type 2 diabetes. Using a state-of-the-art knowledge-based recommendation system as a reference, we assessed the meal plans generated by two large language models in terms of energy intake, nutrient accuracy, and meal variability. Experimental results with different user profiles revealed the potential of ChatGPT models to provide personalized nutritional advice. Additional supervision and guidance by nutrition experts or knowledge-based systems are required to ensure meal appropriateness for users with NCDs.

Papastratis I ，Stergioulas A ，Konstantinidis D ，Daras P ，Dimitropoulos K ... -  《-》

AI nutrition recommendation using a deep generative model and ChatGPT.

In recent years, major advances in artificial intelligence (AI) have led to the development of powerful AI systems for use in the field of nutrition in order to enhance personalized dietary recommendations and improve overall health and well-being. However, the lack of guidelines from nutritional experts has raised questions on the accuracy and trustworthiness of the nutritional advice provided by such AI systems. This paper aims to address this issue by introducing a novel AI-based nutrition recommendation method that leverages the speed and explainability of a deep generative network and the use of novel sophisticated loss functions to align the network with established nutritional guidelines. The use of a variational autoencoder to robustly model the anthropometric measurements and medical condition of users in a descriptive latent space, as well as the use of an optimizer to adjust meal quantities based on users' energy requirements enable the proposed method to generate highly accurate, nutritious and personalized weekly meal plans. Coupled with the ability of ChatGPT to provide an unparalleled pool of meals from various cuisines, the proposed method can achieve increased meal variety, accuracy and generalization capabilities. Extensive experiments on 3000 virtual user profiles and 84000 daily meal plans, as well as 1000 real profiles and 7000 daily meal plans, demonstrate the exceptional accuracy of the proposed diet recommendation method in generating weekly meal plans that are appropriate for the users in terms of energy intake and nutritional requirements, as well as the easiness with which it can be integrated into future diet recommendation systems.

Papastratis I ，Konstantinidis D ，Daras P ，Dimitropoulos K ... -  《Scientific Reports》

PROTEIN AI Advisor: A Knowledge-Based Recommendation Framework Using Expert-Validated Meals for Healthy Diets.

Stefanidis K ，Tsatsou D ，Konstantinidis D ，Gymnopoulos L ，Daras P ，Wilson-Barnes S ，Hart K ，Cornelissen V ，Decorte E ，Lalama E ，Pfeiffer A ，Hassapidou M ，Pagkalos I ，Argiriou A ，Rouskas K ，Hadjidimitriou S ，Charisis V ，Dias SB ，Diniz JA ，Telo G ，Silva H ，Bensenousi A ，Dimitropoulos K ... -  《Nutrients》

Can the AI tools ChatGPT and Bard generate energy, macro- and micro-nutrient sufficient meal plans for different dietary patterns?

Artificial intelligence chatbots based on large language models have recently emerged as an alternative to traditional online searches and are also entering the nutrition space. In this study, we wanted to investigate whether the artificial intelligence chatbots ChatGPT and Bard (now Gemini) can create meal plans that meet the dietary reference intake (DRI) for different dietary patterns. We further hypothesized that nutritional adequacy could be improved by modifying the prompts used. Meal plans were generated by 3 accounts for different dietary patterns (omnivorous, vegetarian, and vegan) using 2 distinct prompts resulting in 108 meal plans total. The nutrient content of the plans was subsequently analyzed and compared to the DRIs. On average, the meal plans contained less energy and carbohydrates but mostly exceeded the DRI for protein. Vitamin D and fluoride fell below the DRI for all plans, whereas only the vegan plans contained insufficient vitamin B12. ChatGPT suggested using vitamin B12 supplements in 5 of 18 instances, whereas Bard never recommended supplements. There were no significant differences between the prompts or the tools. Although the meal plans generated by ChatGPT and Bard met most DRIs, there were some exceptions, particularly for vegan diets. These tools maybe useful for individuals looking for general dietary inspiration, but they should not be relied on to create nutritionally adequate meal plans, especially for individuals with restrictive dietary needs.

Hieronimus B ，Hammann S ，Podszun MC 《-》

Is ChatGPT an Effective Tool for Providing Dietary Advice?

Ponzo V ，Goitre I ，Favaro E ，Merlo FD ，Mancino MV ，Riso S ，Bo S ... -  《Nutrients》