领域(数学)
人工智能
计算机科学
数据科学
深度学习
机器学习
数学
纯数学
作者
Mélina Côté,Benoı̂t Lamarche
出处
期刊:Elsevier eBooks
[Elsevier BV]
日期:2024-01-01
卷期号:: 465-473
标识
DOI:10.1016/b978-0-443-15688-5.00031-0
摘要
This chapter summarizes the current applications of artificial intelligence (AI), mainly machine learning, deep learning, and natural language processing, in three main fields in nutrition research and practice. First, we describe AI-based approaches that have been employed to improve dietary assessment tools, notably to analyze audio recordings, motion sensors, and images to recognize and measure dietary intakes. Second, we discuss AI-based methods that have advanced the field of precision nutrition through an enhanced capacity to manage and analyze voluminous data in genomics, metabolomics, and microbiomics. Third, we describe how the field of public health nutrition has benefited from AI through the development of more flexible prediction models in nutritional epidemiology and in the monitoring of health using geotagged data. Finally, this chapter ends with a brief discussion of the main challenges and limitations of AI applications in the field of nutrition.
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