Abstract: OBJECTIVE: To investigate the potential rules and knowledge of Traditional Chinese Medicine (TCM) and Western Medicine (WM) treatment on chronic urticaria (CU) based on data-mining methods. METHODS: Sixty patients with chronic urticaria, treated with TCM and WM, were selected. Gray correlation analyses were adopted to determine therapeutic efficacy. Association algorithms were utilized to ascertain the correlation between the disease course and treatment results. A genetic algorithm was applied to discover the optimization model in theTCM andWM treatment on CU. RESULTS: The total symptom scores after 4 weeks and 8 weeks of treatment in the TCM spleen-strengthening group correlated highly with the pretreatment total symptom score. The duration of treatment showed the greatest impact on the total symptom score. A quartic equation was established (y=-1.6403×10-6x4+0.00025576x3+0.0012819 x2-1.024x+79.5879, and x=106.9518, y=83.0036) using the genetic algorithm. CONCLUSION: TCM treatment had a better effect in the later stage, whereas WM was better in the early stage. The duration of disease course had an impact on the effects of treatment. If the average total symptom score before treatment was ≤ 83.0036, TCM or WM treatment could achieve better efficacy.

Key words: Urticaria, Algorithm, Data mining, Traditional Chinese Medicine, Western Medicine