Machine Learning in Nutritional Science: Personalizing Diets with Precision Algorithms
Authors:-Lubna Tabasum
Abstract-:Machine learning (ML) is revolutionizing nutritional science by enabling the personalization of diets based on individual health conditions, genetic profiles, and lifestyle factors. This paper explores the role of machine learning in enhancing dietary recommendations and improving health outcomes. It discusses how ML algorithms can analyze large datasets of nutritional information, medical histories, and genomic data to create tailored dietary plans that optimize nutrition for individuals. The paper highlights the integration of AI technologies in the development of precision nutrition models, the benefits of personalized diets in managing chronic diseases, and the emerging trends in nutrition prediction. The challenges of data privacy, model interpretability, and the need for interdisciplinary collaboration between nutritionists, data scientists, and clinicians are also examined. The paper concludes by discussing the future of machine learning in nutritional science, emphasizing the potential of combining AI with wearable technologies to continuously monitor and adjust diets for long-term health optimization.
