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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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Artificial Intelligence in Malnutrition: A Systematic Literature Review

Details
Category: Nutrition, Data Science and Artificial Intelligence
Hits: 76
ID: 102
  • Study Status: Published
  • Study Type: Review
  • Study Location: Global

Study Title
Artificial Intelligence in Malnutrition: A Systematic Literature Review

Principal Investigator
Sander MW Janssen, Yamine Bouzembrak, Bedir Tekinerdogan

Affiliation
Wageningen University and Research, The Netherlands

Start Date
Not specified

End Date
Not specified

Study Objective
To review the application of artificial intelligence (AI) in detecting and diagnosing malnutrition, including identifying patient groups, tools used, machine learning algorithms, and challenges in implementation.

Short Abstract
This systematic literature review explores the use of AI in malnutrition diagnosis and screening, focusing on machine learning (ML) techniques for early detection of malnutrition. Despite the progress, over 90% of AI models developed for malnutrition detection remain unused in clinical practice. The study identifies the most common patient groups, algorithms, and tools, as well as challenges in integrating AI models into routine care.

Study Design
Systematic literature review

Population
Global, focusing on clinical settings for malnutrition detection

Sample Size
334 articles screened, 49 studies included

Inclusion Criteria
Studies using AI and machine learning for malnutrition diagnosis and screening in clinical settings

Exclusion Criteria
Studies not focusing on AI-based malnutrition tools

Intervention/Exposure
AI and machine learning-based decision support systems (DSS) for malnutrition detection

Outcome Measures

  • Type of malnutrition tools used
  • Types of machine learning algorithms employed
  • Implementation stage of AI tools

Funding Source
Not specified

Collaborating Institutions
Wageningen University and Research

Ethics Approval
Not specified

Publication Status
Published in Advances in Nutrition (2024)

Keywords
Machine learning, malnutrition, AI, decision support systems, nutritional screening

Data Collection Methods
Systematic literature review of articles from PubMed, Scopus, Google Scholar, and Web of Science

Primary Data Availability
Available upon request to the corresponding author

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