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Data Science for Personalized Nutrition Harnessing Big Data for Tailored Dietary Recommendations
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Author(s): Sandip J. Gami (Independent Researcher, USA), Balaji Dhamodharan (Independent Researcher, USA), Pushan Kumar Dutta (Amity University, Kolkata, India), Vaibhav Gupta (Threws, India)and Pawan Whig (VIPS, India)
Copyright: 2024
Pages: 25
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.ch023
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Abstract
The advent of data science has revolutionized various sectors, with personalized nutrition emerging as a significant beneficiary. This chapter explores the integration of data science techniques in developing tailored dietary recommendations. By leveraging big data, including genomic, phenotypic, and lifestyle information, personalized nutrition aims to optimize health and prevent diseases. The authors delve into the methodologies for data collection, analysis, and interpretation, highlighting the role of machine learning algorithms in predicting individual nutritional needs. Case studies and real-world applications are discussed to illustrate the practical benefits and challenges of implementing personalized nutrition strategies. This chapter aims to provide a comprehensive understanding of how data science can transform nutrition into a highly individualized and effective approach to health and well-being.
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