Inquiry diagnosis of coronary heart disease in Chinese medicine based on symptom-syndrome interactions

Guo-Zheng Li,Ya-Lei Wang,Guo-Ping Liu,Mingyu You,Sheng Sun

doi:10.1186/1749-8546-7-9

Abstract

BackgroundThere 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.MethodsRelative 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.ResultsAnalysis 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.ConclusionThe 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.

Highlights

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
In CM, a symptom represents an observable indicator of abnormality, while a syndrome is the disease state manifested by symptoms
This study aims to use Relative associated density (RAD) to perform symptom selection, and evaluate whether the results can be better explained by CM theory [12,13]

Summary

Introduction

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. Western medicine classifies coronary heart disease (CHD) as a kind of myocardial dysfunction and organic lesion, occasionally accompanied by coronary artery stenosis and vertebrobasilar insufficiency [1]. Chinese medicine (CM) classifies CHD as a type of chest paralysis and heart pain, for which effective diagnosis and treatment are available [2]. Wang et al [6] used a decision tree method to generate prediction models for CM hepatitis data and liver cirrhosis data. Zhang et al [7] combined factor and cluster analysis in the classification of CM syndromes related to post-hepatitic cirrhosis. Zhang et al [8] used latent tree models to aid CM diagnosis. Knowledge discovery in database (KDD) [9], rough set [10], and expert system [11], have been applied to CM

Objectives

Methods

Results