Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective
المؤلفون المشاركون
Wang, Chengjun
Niu, Jinling
Zhao, Changbo
Li, Guo-zheng
المصدر
Evidence-Based Complementary and Alternative Medicine
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-18، 18ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-07-12
دولة النشر
مصر
عدد الصفحات
18
التخصصات الرئيسية
الملخص EN
As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas.
In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM).
Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signsexamined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes ofdisease occurrence and development.
Patient classification is to divide patients into several classes based on different criteria.
In this paper, from the machine learning perspective, a survey onpatient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification.
With the consideration of different diagnosticdata analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively.
For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction.
According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhao, Changbo& Li, Guo-zheng& Wang, Chengjun& Niu, Jinling. 2015. Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective. Evidence-Based Complementary and Alternative Medicine،Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1061425
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhao, Changbo…[et al.]. Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective. Evidence-Based Complementary and Alternative Medicine No. 2015 (2015), pp.1-18.
https://search.emarefa.net/detail/BIM-1061425
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhao, Changbo& Li, Guo-zheng& Wang, Chengjun& Niu, Jinling. Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective. Evidence-Based Complementary and Alternative Medicine. 2015. Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1061425
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1061425
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