Background: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at the intricate connection between food and health in both an individual and a community context. AI also helps in tracing and offering solutions in dietary assessment, personalized and clinical nutrition, as well as disease prediction and management, such as cardiovascular diseases, diabetes, cancer, and obesity. This review aims to investigate and assess the different applications and roles of AI in nutrition and research and understand its potential future impact. Methods: We used PubMed, Scopus, Web of Science, Google Scholar, and EBSCO databases for our search. Results: Our findings indicate that AI is reshaping the field of nutrition in ways that were previously unimaginable. By enhancing how we assess diets, customize nutrition plans, and manage complex health conditions, AI has become an essential tool. Technologies like machine learning models, wearable devices, and chatbot applications are revolutionizing the accuracy of dietary tracking, making it easier than ever to provide tailored solutions for individuals and communities. These innovations are proving invaluable in combating diet-related illnesses and encouraging healthier eating habits. One breakthrough has been in dietary assessment, where AI has significantly reduced errors that are common in traditional methods. Tools that use visual recognition, deep learning, and mobile applications have made it possible to analyze the nutrient content of meals with incredible precision. Conclusions: Moving forward, collaboration between tech developers, healthcare professionals, policymakers, and researchers will be essential. By focusing on high-quality data, addressing ethical challenges, and keeping user needs at the forefront, AI can truly revolutionize nutrition science. The potential is enormous. AI is set to make healthcare not only more effective and personalized but also more equitable and accessible for everyone.

Hybrid learning enables educators to incorporate elements of conventional face-to-face learning methods with structured online schemes. This study aimed to assess university students’ perceptions of online and hybrid learning during the ongoing COVID-19 pandemic. A web-based cross-sectional study was conducted at the University of Sharjah, in the United Arab Emirates (n = 2056). Students’ sociodemographic characteristics, perceptions of online and hybrid learning, concerns, and university life changes, were investigated. Perception statements were dichotomized into "positive" and "negative" based on a 50% cut-off point. Scores of > 7 and >5 indicated positive perceptions of online and hybrid learning respectively while scores of ≤ 7 and ≤ 5 indicated negative perceptions. Binary logistic regression analysis was performed to predict students’ perceptions of online and hybrid learning according to demographic variables. Spearman’s rank-order correlation was performed to determine the relationship between students’ perceptions and behaviors. Most students preferred online learning (38.2%) and on-campus learning (36.7%) to hybrid learning (25.1%). Around two-thirds of the students had a positive perception of online and hybrid learning in terms of university support, however, half of them preferred the assessment during online or on-campus learning. Main difficulties reported in hybrid learning were lack of motivation (60.6%), discomfort when on-campus (67.2%), and distraction due to mixed methods (52.3%). Older students (p = 0.046), men (p<0.001), and married students (p = 0.001) were more likely to have a positive perception of online learning, while sophomore students were more likely to have a positive perception of hybrid learning (p = 0.001). In this study, most students preferred online or on-campus over hybrid learning and expressed certain difficulties while on hybrid learning. Future research should focus on investigating the knowledge and capability of graduates from a hybrid/online model compared to a traditional model. Obstacles and concerns should be considered for future planning to ensure the resilience of the educational system.

Restaurant menu calorie labeling is regarded as a promising, cost-effective, and innovative method that will have an impact on the food environment, raise awareness among consumers, and aid in global efforts to prevent obesity. This study aimed to assess the public’s calorie literacy, dining practices, and perceived effectiveness of restaurant menu labeling implementation in the United Arab Emirates (UAE). A descriptive, web-based cross-sectional study was conducted among 1279 adults in the UAE. Socio-demographic characteristics, calorie literacy, and perceived effectiveness of restaurant menu labeling among participants were investigated. Chi-square analysis was used to compare indicators across demographic characteristics. More females than males completed the online survey, (56.1% and 43.9%). Most of the participants aged < 30 years old (54.8%), The majority of participants reported eating away from home at least once per week (89.6%). 66.0% of participants were knowledgeable about calorie definition, but only 37.1% knew about average daily energy requirements. Younger participants, with a normal BMI, and higher education levels reported a significantly higher likelihood of eating at a chain restaurant with caloric information on the menu (p <0.05). The majority of participants (76.0%) preferred to see calorie information and other nutrition information on menus. To conclude, menu labeling is a welcomed policy to be implemented in food outlets. Further investigation is necessary to ascertain the most efficacious method of presenting nutrition information to consumers to facilitate informed purchasing decisions considering the potential benefits of mandating calorie declaration in obesity prevention efforts.