天津中医药2024，Vol.41Issue(7)：829-834,6.DOI:10.11656/j.issn.1672-1519.2024.07.04
基于数据挖掘技术的肺结节常见证候诊断依据分析
Analysis of common syndromes diagnosis basis of pulmonary nodules based on data mining
摘要
Abstract
[Objective]To preliminarily establish the diagnosis basis for common syndromes of pulmonary nodules.[Methods]The correlation between symptoms and their contribution to common syndromes was analyzed using association rules combined with a Bayesian network based on the clinical data of 746 clinical data of pulmonary nodules.[Results]Among the common syndromes,the closely related symptom groups and their contribution to the syndrome were as follows:1)lung qi deficiency syndrome:fatigue & spiritual tiredness(0.22);2)lung spleen qi deficiency syndrome:cough & white phlegm(0.27),cough & shortness of breath(0.19),white greasy tongue fur & thin tongue(0.57),thin tongue & fine weak pulse(0.36),fatigue & poor appetite(0.14);3)phlegm turbid obstructing the lung syndrome:cough & white phlegm(0.32),chest tightness & shortness of breath(0.19).The syndrome of stasis obstructing lung collateral has not yet obtained a closely related symptom group.Conclusion based on the contribution of symptom clusters to common syndromes,the preliminary establishment of diagnostic conditions and basis can provide an objective basis for the establishment of diagnostic criteria for pulmonary nodules syndromes.The symptom clusters that contribute to the stasis lung collateral syndrome need to be further studied.[Conclusion]Based on the correlated symptom clusters and their contribution to syndromes,the diagnostic basis for common syndromes of pulmonary nodules were formed,which can provide a basis for the establishment of diagnostic criteria for pulmonary nodule common syndromes.However,the symptom clusters that contribute to the stasis lung collateral syndrome need to be further studied.关键词
肺结节/常见证候/症状/贡献度/诊断依据Key words
pulmonary nodules/common syndrome/symptom/contribution degree/diagnosis basis分类
医药卫生引用本文复制引用
孙雪鸽,赵虎雷,焦莉,周淼,王中超,黄艳,蒋艳丽,刘元元,李建生..基于数据挖掘技术的肺结节常见证候诊断依据分析[J].天津中医药,2024,41(7):829-834,6.基金项目
国家中医药领军人才支持计划—岐黄学者资助(国中医药人教函[2018]284号) （国中医药人教函[2018]284号）
河南省卫生健康委国家中医临床研究基地科研专项(2021JDZY029) （2021JDZY029）
河南省高等学校重点科研项目(21A360007). （21A360007）
