Based on Data Mining:Analysis of Medication Rules and Clinical Experience for Asthenia

Corresponding author: qinzujie, 109741754@qq.com

DOI: 10.12201/bmr.202507.00063

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  Abstract: Objective The medication patterns and clinical experience of Professor Qin Zujie in the treatment of deficiency labor were explored by using Excel 2021, SPSS Modeler 18.0 and SPSS Statistics27.0.1. Methods The medical cases and prescriptions of Professor Qins outpatient diagnosis of deficiency labor from January 2024 to December 2024 were collected to construct a database and undergo standardized processing. His medication characteristics and diagnosis and treatment experience were analyzed through statistical methods such as frequency statistics, association rule analysis, and cluster analysis. Results A total of 148 valid outpatient prescriptions were screened, involving 171 herbal medicines with a cumulative frequency of 2,109. Twenty Chinese and Zhuang medicines had frequencies >30, with the top five being Glycyrrhizae Radix Praeparata,Atractylodis Macrocephalae Rhizoma,Angelicae Sinensis Radix,Astragali Radix,and Bupleuri Radix. Statistical analysis of herb properties revealed that warm, neutral, and slightly cold natures were predominant; sweet, pungent, and bitter flavors were most common; the spleen meridian was the primary channel tropism; and tonifying herbs (especially qi-tonifying herbs) were the most frequently used. Association rule mining identified the top three herb pairs as Atractylodis Macrocephalae Rhizoma-Codonopsis Radix,Atractylodis Macrocephalae Rhizoma-Cimicifugae Rhizoma, and Angelicae Sinensis Radix-Cimicifugae Rhizoma. Cluster analysis yielded three core prescription patterns. Conclusion Professor Qin’s medication rules for consumptive disease can be summarized as: (1) Emphasizing qi and blood regulation while harmonizing the spleen and stomach; (2) Nourishing both innate and acquired constitutions to consolidate fundamental health; and (3) Prioritizing tonification while incorporating detoxification for holistic treatment.

  Key words: Asthenia; Medication Rules; Data Mining; Clinical Experience

  Submit time: 20 July 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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