Data Mining Based Clinical Laboratory Test Data And Diagnosis Of Ovarian Tumors

OBJECTIVE: To study the relevant indicators of clinical examination and inspection items in the electronic medical records of ovarian malignant tumors,to study the correlation rules between clinical examination results and ovarian malignancy,and to further explore the existing results of various clinical examination and ovarian cancer The association provides a reference for early diagnosis of ovarian malignancy.Methods: The data was preprocessed by using SQL database technology.The relationship between the test results and the diagnosis of ovarian malignancy was analyzed by using association rules technique and artificial neural network in association analysis.Results: A total of 233 electronic medical records were selected in2008.Data of 109 clinical examination related indicators were included in the data analysis.Data of 10 clinical test results and the diagnosis ofovarian malignancy were explored.A better ovarian tumor marker was proposed.Classification prediction method.Conclusion: The association rule classification method derived from data mining of malignant ovarian cancer electronic medical records can provide a good reference for the diagnosis of ovarian malignant tumors.On the other hand,it can also improve the survival rate of ovarian cancer patients.