Core reference ontology for individualized exercise prescription

Abstract “Exercise is medicine” emphasizes personalized prescriptions for better efficacy. Current guidelines need more support for personalized prescriptions, posing scientific challenges. Facing those challenges, we gathered data from established guidelines, databases, and articles to develop the...

Full description

Saved in:
Bibliographic Details
Main Authors: Xingyun Liu, Yin Yang, Hui Zong, Ke Zhang, Min Jiang, Chunjiang Yu, Yalan Chen, Ting Bao, Danting Li, Jiao Wang, Tong Tang, Shumin Ren, Juan M. Ruso, Bairong Shen
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-024-04217-9
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract “Exercise is medicine” emphasizes personalized prescriptions for better efficacy. Current guidelines need more support for personalized prescriptions, posing scientific challenges. Facing those challenges, we gathered data from established guidelines, databases, and articles to develop the Exercise Medicine Ontology (EXMO), intending to offer comprehensive support for personalized exercise prescriptions. EXMO was constructed using the Ontology Development 101 methodology, incorporating Open Biological and Biomedical Ontology Foundry principles. EXMO v1.0 comprises 434 classes and 9,732 axioms, encompassing physical activity terms, health status terms, exercise prescription terms, and other related concepts. It has successfully undergone expert evaluation and consistency validation using the ELK and JFact reasoners. EXMO has the potential to provide a much-needed standard for individualized exercise prescription. Beyond prescription standardization, EXMO can also be an excellent tool for supporting databases and recommendation systems. In the future, it could serve as a valuable reference for developing sub-ontologies and facilitating the formation of an ontology network.
ISSN:2052-4463