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Nutrition, Data Science and Artificial Intelligence

The Nutrition, Data Science, and Artificial Intelligence special collection aims to explore the intersection of nutrition science, data analytics, and AI. We invite submissions that leverage advanced computational techniques to analyse large-scale dietary data, predict nutritional outcomes, and develop innovative solutions for personalised dietary recommendations and dietary pattern analysis.
 

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Precision Nutrition: A Systematic Literature Review

Details
Category: Nutrition, Data Science and Artificial Intelligence
Hits: 43
ID: 104
  • Study Status: Published
  • Study Type: Review
  • Study Location: Global

Study Title
Precision Nutrition: A Systematic Literature Review

Principal Investigator
Daniel Kirk, Cagatay Catal, Bedir Tekinerdogan

Affiliation
Wageningen University and Research, the Netherlands; Qatar University, Doha, Qatar

Start Date
Not specified

End Date
Not specified

Study Objective
To provide an overview of the use of machine learning (ML) in precision nutrition (PN), identifying the domains of application, the features used in models, the algorithms employed, and the evaluation metrics for these models.

Short Abstract
This systematic literature review investigates the application of machine learning in precision nutrition, focusing on the use of personal data for delivering individualized nutrition advice. It synthesizes 60 primary studies from 4930 retrieved papers, analyzing ML tasks, algorithms, and features used for various PN-related problems. The review highlights the potential of ML in improving the effectiveness of personalized nutrition.

Study Design
Systematic literature review

Population
Global studies on precision nutrition and machine learning

Sample Size
4930 papers screened, 60 primary studies selected

Inclusion Criteria
Studies applying machine learning to precision nutrition or related areas like dietary intake, metabolic health, bodyweight management, etc.

Exclusion Criteria
Studies not related to human nutrition or machine learning, articles not available in full, non-primary studies (e.g., reviews, commentaries)

Intervention/Exposure
Machine learning techniques applied to personalized nutrition

Outcome Measures

  • Domains of application for machine learning in PN
  • Features used in machine learning models
  • Algorithms and evaluation metrics

Funding Source
Not specified

Collaborating Institutions
Wageningen University and Research, Qatar University

Ethics Approval
Not specified

Publication Status
Published in Computers in Biology and Medicine (2021)

Keywords
Precision nutrition, personalized nutrition, machine learning, deep learning, systematic review

Data Collection Methods
Systematic literature review from databases like Web of Science, Scopus, PubMed, and ScienceDirect

Primary Data Availability
Not applicable

Contact Information
Daniel Kirk: This email address is being protected from spambots. You need JavaScript enabled to view it.