The intelligent experience inheritance system for Traditional Chinese Medicine

Abstract

The inheritance of knowledge and experience was crucial to the development of Traditional Chinese Medicine (TCM). However, the existing methods of inheriting the unique clinical experience of famous veteran TCM doctors still followed the outdated and inefficient Master‐Prentice schema. In addition, the inherited medical books and records were usually lack of standardization and systematization. In this article, a new method for inheriting the academic thoughts and clinical experience of famous veteran doctors with the help of artificial intelligence technology was explored. Due to the individualized treatment characteristics namely “same disease with different treatments, different diseases with the same treatment,” the intelligent inheritance of TCM faced many technical barriers. To tackle these problems, we proposed a prototype system framework for the intelligent inheritance of famous veteran doctors based on rules and deep learning models and performed a case study on the treatment of pediatric asthma. The architecture could not only make full use of the advantages of deep learning, but also integrate the valuable knowledge and experience analysis of famous veteran doctors from injected rules. Specifically, the study took pediatric asthma medical records as training and test samples and calculated the similarity between the generated prescriptions and the real‐world clinical prescriptions from the famous veteran doctors. Experimental results showed that the generated prescription could achieve a similarity of more than 90%. It proved that the proposed framework provided a feasible way for the intelligent inheritance and research of the academic thoughts and clinical experience of famous veteran TCM doctors.

Internet-Based Healthcare Knowledge Service for Improvement of Chinese Medicine Healthcare Service Quality

“…In view of the combination of new technologies and products such as cloud computing and artificial intelligence derived from internet big data and CM, the modernization of CM is accelerating to achieve leapfrog development, which puts forward higher requirements for CM knowledge services. The research results show that the new generation of information technology can be combined with the academic thinking of CM [36] to provide knowledge services in various aspects such as pharmacological analysis [37], auxiliary diagnosis and treatment [38], and optimization of the diagnosis process [39].…”

Construction of Chinese Medicine Prescription Data Mining Based on Association Rules of the System

“…26 A new method for inheriting the academic thoughts and clinical experience of famous veteran doctors with the help of artificial intelligence technology was explored and a prototype system framework was proposed based on rules and deep learning models, which was demonstrated as a feasible way. 27 A decision tree method based on information entropy was applied to explore TCM syndrome differentiation of chronic gastritis. Using the bootstrap method to amplify 406 cases, the decision tree algorithm C4.5 was used to determine the coincidence rate of model classification, and the results were as follows: 83.60% for the training set, 80.67%, and 81.25% for the test set.…”