Objective:To achieve rapid recommendation of decoction parameters for intelligent decoction equipment of traditional Chinese medicine(TCM)decoction,a multi-dimensional similarity algorithm integrating classical formulas was proposed to provide personalized decoction recommendations by drawing on ancient classical prescriptions.Methods:Thirty classical prescriptions were selected,and the decoction parameters recommended by the algorithm were compared with those recorded in ancient texts.The Jac-card similarity coefficient,cosine similarity,and Latent Dirichlet Allocation(LDA)topic model similarity algorithms were employed to calculate the similarity between experimental formulas and those in the decoction database,based on the composition,dosage,and functional characteristics of TCM compound formulas.The decoction parameters of the most similar formulas in each dimension were weighted and integrated to obtain personalized decoction parameters for the thirty classical prescriptions.Results:The relative errors in water volume,strong fire duration,and mild fire duration were 5.3％,3.4％,and 7.1％,respectively.Conclusion:The two sets of decoction parameters were relatively close,effectively drawing on and inheriting the decoction techniques of classical prescrip-tions.
Traditional Chinese medicine decoction/Personalized decoction/Multi-dimension/LDA topic model/Formula simi-larity/Cosine of included angle/Jaccard similarity coefficient
维普
万方数据