A Review on the Potencies of AI-Driven Nutritional Assessment Studies in Enhancing Public Health

Abstract

Proper nutrition is essential for promoting a healthy and productive life. Nutritional assessment plays a crucial role in formulating effective public health strategies to combat the global issue of malnutrition. However, traditional assessment methods often rely on time-consuming and self-reported data, leading to potential inaccuracies. The emergence of Artificial Intelligence (AI) offers promising solutions to revolutionize nutritional science. This review explores how AI can transform various aspects of nutritional assessment. AI, incorporating machine learning, natural language processing, computer vision, and robotics, leverages data analysis, pattern recognition, and personalized nutrition recommendations. By analysing extensive datasets, including dietary preferences, health records, and genetic information, AI can create personalized nutrition plans, suggest healthier food alternatives, manage nutrition-related diseases, enhance food safety, optimize food supply chains, and design balanced menus for different settings. AI-driven technologies ensure more robust, rapid, and accurate nutritional assessment, benefiting diverse vulnerable groups. Nevertheless, ethical considerations, such as bias in algorithms, privacy concerns, and potential job impacts, require careful attention. Prioritizing data protection, privacy, and responsible AI development will facilitate the integration of AI in nutritional assessment, leading to transformative advancements while safeguarding individuals' rights and well-being.