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BACKGROUND Knowledge discovery from treatment data records from prestigious Chinese physicians is a dramatic challenge in the applications of artificial intelligence models to the research of Traditional Chinese Medicine (TCM). OBJECTIVE This paper aims to construct a TCM knowledge graph from prestigious Chinese physicians and apply it to decision-making assistant of TCM diagnosis and treatment. METHODS A new framework leveraging a representation learning method for TCM knowledge graph construction and application is designed. A Transformer-based Contextualized Knowledge Graph Embedding (CoKE) model is applied to knowledge graph representation learning and knowledge distillation. Automatic identification and expansion of multi-hop relations are integrated with the CoKE model as a pipeline. Based on the framework, a TCM knowledge graph, containing 598,82 entities including diseases, symptoms, examinations, drugs, etc., 17 relations, and 604,700 triples, is constructed. The framework is validated through a link predication task. RESULTS Experiments show that the framework outperforms a set of baseline models in the link prediction task using standard metrics MRR and Hits@N. The knowledge embedding multi-tagged TCM discriminative diagnosis metrics also indicates the improvement of our framework compared with the baseline models CONCLUSIONS Experiments show that the clinical knowledge graph representation learning and application framework is effective for knowledge discovery and decision-making assistance in diagnosis and treatment . Our framework shows superiority of application prospects in tasks such as knowledge graph fused multi-modal information diagnosis, knowledge graph embedding based text classification and knowledge inference based medical question answering.

MLD system is a type of hybrid system, which adopts the form of integer linear inequality including continuous variable and logical variable, which reflects both continuous and discrete dynamic characteristics by switching law. In this paper, the problem of optimal management of open laboratories in Colleges and universities is illustrated in the form of a class of advanced MLD system. By analyzing the main factors of laboratory consumption, the laboratory cost function is established. Taking the minimum cost as the objective function, it uses the random number of students in the laboratory to realize the energysaving optimization management of the laboratory. At the end of this paper, a simulation example is used to analyze the process of MLD system used in laboratory optimization management, which shows hybrid dynamic characteristics, optimal management effect and ideal applicability.

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