Discussion of Standardized Model for Hyperlipidemia Syndrome Based on Text Mining
Objective To explore the construction of a standardized model for hyperlipidemia syndrome based on literature anal-ysis.Methods By studying the literature related to the symptoms and syndrome differentiation of hyperlipidemia from January 1,2000 to December 1,2022,the main symptoms were summarized,and the results were cluster validated.Results A total of 24 arti-cles were included,and 132 valid symptom and syndrome data were extracted.65 syndrome types were obtained by combining simi-lar symptoms.Standardize the syndrome types that appear,and summarize the top 5 according to the cumulative frequency of clini-cal case reports,which are phlegm turbidity resistance syndrome,spleen and kidney yang deficiency syndrome,liver depression and spleen deficiency syndrome,qi stagnation and blood stasis syndrome,and liver and kidney yin deficiency syndrome.This result is consistent with the main syndrome types verified by cluster analysis.Conclusion Using text mining combined with professional knowledge to study literature related to traditional Chinese medicine syndromes is a beneficial exploration for standardizing syn-drome research.Cluster analysis,as one of the important algorithms in data mining,can provide objective basis for determining syn-dromes.
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