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Mining Symptom-Herb Patterns from Patient Records Using Tripartite Graph
Joint Authors
Poon, Simon
Sze, Daniel Man-yuen
Poon, Josiah
Chen, Jinpeng
Xu, Ling
Source
Evidence-Based Complementary and Alternative Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-08
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Unlike the western medical approach where adrug is prescribed against specific symptoms of patients,traditional Chinese medicine (TCM) treatment has a uniquestep, which is called syndrome differentiation (SD).
It is arguedthat SD is considered as patient classification because priorto the selection of the most appropriate formula from a setof relevant formulae for personalization, a practitioner hasto label a patient belonging to a particular class (syndrome)first.
Hence, to detect the patterns between herbs and symptomsvia syndrome is a challenging problem; finding thesepatterns can help prepare a prescription that contributes tothe efficacy of a treatment.
In order to highlight this uniquetriangular relationship of symptom, syndrome, and herb, wepropose a novel three-step mining approach.
It first startswith the construction of a heterogeneous tripartite informationnetwork, which carries richer information.
The second step isto systematically extract path-based topological features fromthis tripartite network.
Finally, an unsupervised method is usedto learn the best parameters associated with different featuresin deciding the symptom-herb relationships.
Experiments havebeen carried out on four real-world patient records (Insomnia, Diabetes, Infertility, and Tourette syndrome) with comprehensivemeasurements.
Interesting and insightful experimental resultsare noted and discussed.
American Psychological Association (APA)
Chen, Jinpeng& Poon, Josiah& Poon, Simon& Xu, Ling& Sze, Daniel Man-yuen. 2015. Mining Symptom-Herb Patterns from Patient Records Using Tripartite Graph. Evidence-Based Complementary and Alternative Medicine،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1061502
Modern Language Association (MLA)
Chen, Jinpeng…[et al.]. Mining Symptom-Herb Patterns from Patient Records Using Tripartite Graph. Evidence-Based Complementary and Alternative Medicine No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1061502
American Medical Association (AMA)
Chen, Jinpeng& Poon, Josiah& Poon, Simon& Xu, Ling& Sze, Daniel Man-yuen. Mining Symptom-Herb Patterns from Patient Records Using Tripartite Graph. Evidence-Based Complementary and Alternative Medicine. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1061502
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1061502