Abstract:
BACKGROUND:There is a long history of coronary heart disease (CHD) diagnosis and treatment in Chinese medicine (CM), but a formalized description of CM knowledge is still unavailable. This study aims to analyze a set of CM clinical data, which is important and urgent. METHODS:Relative associated density (RAD) was used to analyze the one-way links between the symptoms or syndromes or both. RAD results were further used in symptom selection. RESULTS:Analysis of a dataset of clinical CHD diagnosis revealed some significant relationships, not only between syndromes but also between symptoms and syndromes. Using RAD to select symptoms based on different classifiers improved the accuracy of syndrome prediction. Compared with other traditional symptom selection methods, RAD provided a higher interpretability of the CM data. CONCLUSION:The RAD method is effective for CM clinical data analysis, particular for analysis of relationships between symptoms in diagnosis and generation of compact and comprehensible symptom feature subsets.
journal_name
Chin Medjournal_title
Chinese medicineauthors
Li GZ,Sun S,You M,Wang YL,Liu GPdoi
10.1186/1749-8546-7-9subject
Has Abstractpub_date
2012-04-05 00:00:00pages
9issue
1issn
1749-8546pii
1749-8546-7-9journal_volume
7pub_type
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