Based On Data Mining Technology To Explore Professor Liu Shenlin’s Clinical Experience Of Differentiation And Treatment Of Esophageal Cancer With Traditional Chinese Medicine

Objective:Based on data mining technology,this study comprehensively summarizes and extractes the academic thought core of Professor Liu Shenlin’s treatment of esophageal cancer,concluding the syndrome differentiation system,medication characteristics,drug and syndrome correlation and diagnosis and treatment rules of his treatment of esophageal cancer,so as to lay a foundation for further inheritance of academic experience of famous old experts of Traditional Chinese Medicine.Methods:The clinical cases of diagnosis and treatment of esophageal cancer by Professor Liu Shenlin in Famous doctor Hall of Jiangsu Province Hospital of Traditional Chinese Medicine from September 2006 to September 2020 were collected,including 95 patients and 833 clinical visits.All the medical information was input into Excel item by item.According to the specific data mining requirements,the original data was cleaned to establish a standardized database,and the cleaned data was input into Medcase V3.2 public medical record mining system of TCM vein case data.The data of medical records were processed by FPGrowth algorithm and XMiner Operation Tool,and the complex network relationship among "clinical symptoms-tongue and pulse-therapeutic principles-drug-dose-staging" was explored by combining the thematic model,association rules,multi-factor dimensionality reduction,complex network and other methods.Results:The top ten of clinical symptoms in medical records are swallowing obstruction,cough and expectoration,loose stools,abdominal distension,dry mouth,shortness of breath and fatigue,loss of appetite,acid reflux,chest tightness.The high frequency of tongue image is thin white tongue coating,greasy tongue coating,red tongue texture,light tongue texture,crack,tooth marks and so on.The pulse is mainly thin,stringy and smooth.The main therapeutic methods are invigorating spleen,harmonizing stomach,resolving phlegm,dropping the inverse,removing stasis,detoxifying,regulating qi,nourishing Yin,resolving dampness,soothing liver,etc.The drugs with high frequency were tangerine peel,Fructus aurantii,fried Atractylodes macrocephala,acute semen,fried licorice,Pinellia ternata,Scutellaria barbata,and Shida Chuang,etc.Top two in the frequency of powder are Shougong powder and ginseng notoginseng powder.There were 24 drug pairs,6 clinical symptom K-means cluster values,15 drug K-means cluster values and 35 prescription K-means cluster values.The core prescriptions are Jianpi Xiaoge prescription and Xiaotan Zhuyu prescription.There were two groups of representative cluster prescription in each stage.There are significant differences in symptom scores of swallowing obstruction,cough and expectoration,loss of appetite,acid reflux and chest tightness before and after treatment in the same medical records(P<0.05).Conclusion:Through data mining,two common syndrome types of esophageal cancer treated by Professor Liu Shenlin are summarized:spleen deficiency and stasis toxin type,phlegm and stasis type.Two common prescriptions are Jianpi Xiaoge prescription and Xiaotan Zhuyu prescription.Two common powders are Shougong powder and ginseng notoginseng powder.Each period has different representative prescriptions.The symptoms of swallowing obstruction,cough and expectoration,loss of appetite,acid regurgitation and chest tightness are improved after taking medicine.