In this work, an improved Apriori algorithm is proposed. The main goal is to improve the processing efficiency of the algorithm, and the idea and process of the Apriori algorithm are optimized. The proposed method is compared with the classical association rule algorithm to verify its effectiveness. Traditional Chinese medicine plays a certain role in the prevention and treatment of COVID-19. In order to deeply mine the association rules between Chinese herbal medicines for the prevention and treatment of COVID-19, this improved Apriori algorithm is applied from the retrieved published scientific literature and the guidelines for the prevention and treatment of COVID-19 published all over China. Based on the representation of traditional Chinese medicine data in binary form, the potential core traditional Chinese medicine combinations in the treatment of COVID-19 are identified. The results of association rules of Chinese herbal medicine data obtained from the real database provide an important reference for the analysis of COVID-19 combined treatment of Chinese herbal medicine.

In view of the current affected by the COVID-19 outbreak under the special circumstances, we analysis the online teaching mode of current situation, propose a blended online teaching mode based on "live broadcasting + MOOC", specifically describe how to construct the teaching mode, and use "Tencent-classroom + ZJOOC" with practice of four different courses in Taizhou university as an example, to explain the implementation process and effect of this teaching mode.

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This work presents a data-driven method for identifying the potential core acupoint combination in COVID-19 treatment through mining the association rules from the retrieved scientific literature and guidelines for prevention and treatment of COVID-19 published all over China. It is based on the representation of the acupoint data in a binary form, the use of a novel association rule mining algorithm properly tailored for discovering the relationship of acupoint groups among combinations of different descriptions. The proposed method is applied to the real database of acupoint descriptions collected from published literature and guidelines. The obtained results show the effectiveness of the proposed method.