An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example
المؤلفون المشاركون
Yao, Yuanzhe
Wang, Zeheng
Li, Liang
Lu, Kun
Liu, Runyu
Liu, Zhiyuan
Yan, Jing
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-10-01
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130750
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر