Traditional Chinese medicine (TCM) prescriptions have made great contributions to the treatment of diseases and health preservation. To alleviate the shortage of TCM resources and improve the professionalism of automatically generated prescriptions, this paper deeply explores the connection between symptoms and herbs through deep learning technology, and realizes the automatic generation of TCM prescriptions. Particularly, this paper considers the significance of referring to similar underlying prescriptions as herbal candidates in the TCM prescribing process. Moreover, this paper incorporates the idea of referring to the potential guidance information of corresponding prescriptions when model extracts symptoms representations. To provide a reference for inexperienced young TCM doctors when they prescribe, this paper proposes a dual-branch guidance strategy combined with candidate attention model (DGSCAM) to automatically generate TCM prescriptions based on symptoms text. The format of the data used this paper is the “symptoms-prescription” data pair. The specific method is as follows. First, DGSCAM realizes the extraction of key information of prescription-guided symptoms through a dual-branch network. Then, herbal candidates in the form of prescriptions that can treat symptoms are proposed in view of the compatibility knowledge of TCM prescriptions. To our knowledge, this is the first attempt to use prescriptions as herbal candidates in the prescription generation process. We conduct extensive experiments on a mixed public and clinical dataset, achieving 37.39% precision, 25.04% recall, and 29.99% F1 score, with an average doctor score of 7.7 out of 10. The experimental results show that our proposed model is valid and can generate more specialized TCM prescriptions than the baseline models. The DGSCAM developed by us has broad application scenarios and greatly promotes the research on intelligent TCM prescribing.

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TCM Prescription Generation via Knowledge Source Guidance Network Combined with Herbal Candidate Mechanism

The concept of traditional Chinese medicine has different connotations and extensions in different historical periods. This paper examines the formation and development of the concept of traditional Chinese medicine in the perspective of history, theory and empirical research, and explores the internal connection among different medical systems and between medicine and other disciplines. It attempts to re-define the connotation and extension of the concept of traditional Chinese medicine in the context of the new era, provide references for building the medical community of the Chinese nation and promote the standardization of Chinese medicine terminology, advance the cross-disciplinary construction and establishing a new medical system with the characteristics of openness and tolerance, in order to provide the solution, wisdom and power of traditional Chinese medicine for global health in the process of building a community of human health.

[The concept of traditional chinese medicine:history, theory and empirical research].

The current power system is evolving into a low-inertia system due to the integration of renewable energy resources such as wind power. Virtual inertia can be emulated by power electronic devices to provide the frequency support and can be time-variant. How to control the time-variant virtual nertia after a disturbance becomes a question. In this work, we formulate this problem as an optimal control problem, dynamic programming is employed as an algorithm to deal with it. Then we test this method on a 2-bus system and a 12-bus system, and results verify the effectiveness of the proposed method, and show that the frequency of power system can be well regulated while certain constraints can be strictly satisfied. 

Y. Wang

Papers

[The concept of traditional chinese medicine:history, theory and empirical research].

Controlling time-variant virtual inertia: A dynamic programming approach