A research on syndrome element differentiation based on phenomenology and mathematical method - Enliang Yan; Jialin Song; Chaonan Liu; Wenxue Hong (BMC, 2017)
Abstract Background As an empirical medical system independent of conventional Western medicine (CWM), over thousands of years, traditional Chinese medicine (TCM) has established its own unique method of diagnosis and treatment. The perspective of holism and system in TCM is essentially different from the view of Reductionism in CWM. With the development of modern science and technology, the restriction of reductionism is more and more prominent, and researchers begin to pay more attention to holistic thinking in TCM. Confronted with the above situation, there is an urgent need to explore the diagnosis of TCM by the techniques of modern science. Methods To explore the feasibility of using modern science to describe and realize the diagnosis of TCM, in this paper, a method of syndrome element differentiation based on phenomenology is proposed. The proposed method is implemented by mathematical mapping, and then it is testified through analysis of 670 medical records: Based on the original mapping data between two data sets (set of syndrome elements and set of clinical manifestations), new mapping data is generated, and thus the corresponding quantitative diagnostic results are calculated and evaluated. Finally, knowledge discovery of the diagnosis results based on attribute partial-ordered structure diagram is conducted. Results The value order's matching results between original and new results show that the matched degree of each record is no less than 65%, while there are at least 87% records whose matched degree is more than 80%. In addition, the knowledge discoveries of new results are basically identical with the ones of original results as well. Conclusion Using phenomenology to describe syndrome differentiation should be feasible, and further research on mapping relations between various sets (symptoms, formulas, drugs) of TCM should be conducted and evaluated through clinical trials in future.