An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example
Joint Authors
Yao, Yuanzhe
Wang, Zeheng
Li, Liang
Lu, Kun
Liu, Runyu
Liu, Zhiyuan
Yan, Jing
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-01
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of the proposed model are presented.
To validate the proposed model, an ANN structure is established and trained by two hundred forty-two TCM prescriptions.
These data are gathered and classified from the most famous ancient TCM book, and more than one thousand SE reports, in which two ontology-based attributions, hot and cold, are introduced to evaluate whether the prescription will cause SE or not.
The results preliminarily reveal that it is a relationship between the ontology-based attributions and the corresponding predicted indicator that can be learnt by AI for predicting the SE, which suggests the proposed model has a potential in AI-assisted SE prediction.
However, it should be noted that the proposed model highly depends on the sufficient clinic data, and hereby, much deeper exploration is important for enhancing the accuracy of the prediction.
American Psychological Association (APA)
Yao, Yuanzhe& Wang, Zeheng& Li, Liang& Lu, Kun& Liu, Runyu& Liu, Zhiyuan…[et al.]. 2019. An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1130750
Modern Language Association (MLA)
Yao, Yuanzhe…[et al.]. An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1130750
American Medical Association (AMA)
Yao, Yuanzhe& Wang, Zeheng& Li, Liang& Lu, Kun& Liu, Runyu& Liu, Zhiyuan…[et al.]. An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1130750
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130750