Abstract: This paper introduces a groundbreaking approach to optimize the health benefits of mil- lets as an alternative to vegan through the integration of advanced artificial intelligence (AI) technology. Millets, often overlooked in contemporary diets, are revealed to possess re-markable nutritional properties and disease-fighting capabilities, particularly when analysed through AI-driven methodologies. With inherent antioxidant-rich [1] and an alternative for the gluten-sensitive [2], providing a welcoming reprieve for anyone who has felt the discom- forting aftermath of a wheat-heavy [3] meal attributes, millets offer a versatile and nutritious dietary alternative. Leveraging AI, millets emerge as protagonists in the realm of health and wellness, transcending their traditional role and becoming indispensable components [4] of a balanced diet. This study underscores the transformative potential of combining ancient grains with AI technology, ushering in a new era of vitality and well-being. By harnessing the power of machine learning algorithms, we can unlock unprecedented insights into millet’s nutritional profiles [5], tailoring superfood recommendations to individual health needs and dietary preferences. This fusion of tradition and technology paves the way for a revolution in nutritional science, making personalized health optimization not just a possibility, but a reality.
Keywords: Millets, Alternative to Vegan Diet, Artificial Intelligence in Nutrition, AI-Driven Nutritional Analysis, Antioxidant-Rich Grains, Gluten-Free Alternative, Nutritional Optimization, Machine Learning in Health, Superfood Recommendations, Personalized Health Optimization, Dietary Alternatives to Wheat, Ancient Grains and Modern Technology, Nutritional Science Revolution, Individualized Dietary Recommendations, Health Benefits of Millets, Disease Prevention through Diet, AI-Powered Dietary Insights, Wellness and Nutrition, Balanced Diet with Millets, Fusion of Tradition and Technology in Nutrition.
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DOI:
10.17148/IJARCCE.2024.131104
