Font Size: a A A

A Study On The Methodology Of Quantitative Syndrome Differentiation Of Traditional Chinese Medicine

Posted on:2003-09-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:J HongFull Text:PDF
GTID:1104360065960996Subject:Diagnostics of Chinese Medicine
Abstract/Summary:PDF Full Text Request
It is a natural tendency for Traditional Chinese medicine (TCM), as an very important part of traditional medicine, to be modernized and to become a kind of science holding the properties being able to do quantitative description and analysis by the way to take in the methods and techniques of quantitative analysis. This is determined by the law, which is true for the developmental process of science from qualitative description to quantitative analysis. Medical science has quickly progressed in this direction. Meanwhile, this progress is also involved in the key step to improve the level of clinical research on TCM at present. To promote this advancing process of quantitative analysis for TCM developing, it is an important step for syndrome differentiation of TCM to be put forward with the abilities to make diagnosis quantitatively. Therefore, this research was aimed at the methodological studies systematically for syndrome differentiation. This is done through inducing in the mathematical model of Bayesian network system firstly, which was developed recently to analyze complicated events, and on the basis to keep the important property of the concept of holism undisturbed, which is one of the essential principles in the theoretic system of TCM.This work was composed of following studies.Firstly, a systematic analysis was made on the methodologies used in the past researches on syndrome differentiation of TCM with quantitative methods. Begun at the modes of thinking for syndrome differentiation, a summary was made to review the application of overall, diverging and imaging thinking modes in the process of syndrome differentiating. Following this, advantages, disadvantages and practicaleffectiveness were analyzed for quantitative methods used by various researchers in the study of quantitative syndrome differentiation. As the mathematic basis of quantitative syndrome differentiation, the principles of fuzzy determination, semi-quantitative method, single-factor analysis and multiple-factor analysis have all been applied in this field of study largely. However, no one could be used ideally in the quantitative study of syndrome differentiation, because of their own intrinsic faults. As the developing of principles of artificial intelligence and popularizing of bionic intelligence computer technique, the application of artificial (network) intelligent techniques in the field of syndrome differentiation research should be the new tendency of development.Secondly, an investigation was carried out on the laws and methods of thinking in syndrome differentiation of TCM. Started at the analysis of correlations among several main methodologies used for syndrome differentiation, syndrome differentiation union system (SDUS) was more carefully discussed based on the principles put forward by Prof. Zhu Wenfong. Here, the key elements of syndrome differentiation were taken as the key link during the thinking process of syndrome differentiation, i.e. lesion location and lesion nature. The effects, position, and its applying in future in the study of quantitative syndrome differentiation were the main subjects absorbing our attention on SDUS. So, the emphasis of this work was put on the further improvement and implementing program for such a SDUS of symptoms-key elements-syndrome, based on calculation of contribution degree for symptoms/signs to the key elements of syndrome differentiation. Particularly, this paper was focused on the combination between quantitative techniques of syndrome differentiation study and SDUS to make it developing further and for it to be used in the research of quantitative syndrome differentiation in TCM.Thirdly, an investigation was made on the applicability of Bayesian network model used in the quantitative study of TCM syndrome differentiation at the first, based on the analysis as stated above and the review on the newest development in mathematic model of artificial intelligence. The basic consideration for this was on the simulation between Bayesian network model and the th...
Keywords/Search Tags:Syndrome differentiation, Quantitative, Bayesian network, Self-learning, Artificial intelligence, Lesions in the lung system, Medical record
PDF Full Text Request
Related items