Title
Perspective: Towards Automated Tracking of Content and Evidence Appraisal of Nutrition Research
Author
Yang, C.
Hawwash, D.
de Baets, B.
Bouwman, J.
Lachat, C.
Publication year
2020
Abstract
Robust recommendations for healthy diets and nutrition require careful synthesis of available evidence. Given the increasing volume of research articles generated, the retrieval and synthesis of evidence are increasingly becoming laborious and time-consuming. Information technology could help to reduce workload for humans. To guide supervised learning however, human identification of key study characteristics is necessary. Reporting guidelines recommend that authors include essential content in articles and could generate manually labeled training data for automated evidence retrieval and synthesis. Here, we present a semiautomated approach to annotate, link, and track the content of nutrition research manuscripts. We used the STROBE extension for nutritional epidemiology (STROBE-nut) reporting guidelines to manually annotate a sample of 15 articles and converted the semantic information into linked data in a Neo4j graph database through an automated process. Six summary statistics were computed to estimate the reporting completeness of the articles. The content structure, presence of essential study characteristics as well as the reporting completeness of the articles are visualized automatically from the graph database. The archived linked data are interoperable through their annotations and relations. A graph database with linked data on essential study characteristics can enable Natural Language Processing in nutrition. Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.
Subject
Graph database
Reporting guidelines
Research semantics
STROBE-nut
Human
Human experiment
Identification key
Information retrieval
Learning
Natural language processing
Nutrition
Ontology
Practice guideline
Semantics
Standardization
Synthesis
To reference this document use:
http://resolver.tudelft.nl/uuid:3faa41a1-8b8d-49ad-96ff-b6da02bc85f4
DOI
https://doi.org/10.1093/advances/nmaa057
TNO identifier
881675
ISSN
2156-5376
Source
Advances in nutrition, 11 (5), 1079-1088
Document type
article