Intelligent Optimization of Diversified Community Prevention of COVID-19 using Traditional Chinese Medicine

July 28, 2020 · Declared Dead · 🏛 IEEE Computational Intelligence Magazine

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Authors Yu-Jun Zheng, Si-Lan Yu, Jun-Chao Yang, Tie-Er Gan, Qin Song, Jun Yang, Mumtaz Karatas arXiv ID 2007.13926 Category cs.NE: Neural & Evolutionary Cross-listed cs.AI Citations 14 Venue IEEE Computational Intelligence Magazine Last Checked 4 months ago

Abstract

Traditional Chinese medicine (TCM) has played an important role in the prevention and control of the novel coronavirus pneumonia (COVID-19), and community prevention has become the most essential part in reducing the spread risk and protecting populations. However, most communities use a uniform TCM prevention program for all residents, which violates the "treatment based on syndrome differentiation" principle of TCM and limits the effectiveness of prevention. In this paper, we propose an intelligent optimization method to develop diversified TCM prevention programs for community residents. First, we use a fuzzy clustering method to divide the population based on both modern medicine and TCM health characteristics; we then use an interactive optimization method, in which TCM experts develop different TCM prevention programs for different clusters, and a heuristic algorithm is used to optimize the programs under the resource constraints. We demonstrate the computational efficiency of the proposed method and report its successful application to TCM-based prevention of COVID-19 in 12 communities in Zhejiang province, China, during the peak of the pandemic.