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Leveraging Data Science for Personalized Nutrition
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Author(s): Joyeta Ghosh (Department of Dietetics and Applied Nutrition, Amity University, Kolkata, India & School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, UK)
Copyright: 2024
Pages: 34
Source title:
Nutrition Controversies and Advances in Autoimmune Disease
Source Author(s)/Editor(s): Srikanta Patnaik (SOA University, India & Interscience Institute of Management and Technology, India), Ahmed M. Hamad (Benha University, Egypt), Debjyoti Paul (Amity University, Kolkata, India), Pushan Kumar Dutta (Amity University, Kolkata, India)and Muhammad Shafiq (Guangzhou University, China & Shenyang Normal University, China)
DOI: 10.4018/979-8-3693-5528-2.ch022
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Abstract
The field of nutrition is experiencing a remarkable shift towards personalization. The traditional “one-size-fits-all” approach to dietary recommendations is increasingly being challenged by the recognition that individuals have unique genetic, metabolic, and environmental factors that influence their nutritional needs. The objective of the chapter is to delve into the utilization of data science for personalized nutrition. It aims to explore the latest advancements in research concerning the integration of machine learning models to personalize every step of the nutrition care process. This review underscores the prospective role of AI in the realm of clinical nutrition and how such applications could advance care quality while streamlining healthcare provision. By shedding light on this area, the goal is to stimulate discussion, potentially allay concerns, and foster collaborative efforts to optimize the application of AI in clinical nutrition and beyond. It is crucial to acknowledge the extensive and intricate ethical and legal considerations surrounding AI in healthcare.
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