The use of decision tree in diagnosis of breast cancer

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Author:
HU Li-hua(B Ultrasonic Room, Dongfeng Center for Occupational Disease Prevention and Treatment, Hubei Shiyan 442000, China)
WU Jia-bing()
YIN Hong()
LU Rui()
LI Ping()
Journal Title:
Chinese Journal of Biomedical Engineering
Issue:
Volume 18, Issue 03, 2012
DOI:
10.3760/cma.j.issn.1674-1927.2012.03.018
Key Word:
Decision tree;Breast neoplasms;Diagnosis;Fine needle aspiration cytology

Abstract: Objective To explore the use of computer-aided decision tree method in diagnosis of breast cancer,and to provide evidence for the development of computer-assistant diagnosis of breast cancer.Methods Six hundred and ninety-nine cases of breast mass wcrc randomized into two pans,including 70% of cases assigned as the training set for establishing decision tree models and the remaining 30% cases as test set for verification of the effectiveness of these models.The tree module of SPSS was used to establish the classification regulation of decision tree,with 9 indicators of fine needle aspiration cytology (FNAC),as independent variables and the diagnostic results of postoperative pathological examination as dependent vǎriables.Thereafter,the data of test set was input into the established models.The diagnostic results and postoperative pathological diagnosis were then compared for evaluation of the effectiveness of models according to sensitivity,specificity and accuracy rate.Results The sensitivity,specificity and accuracy rate were 92.7%(95%CI:86.2%~99.1%),92.5%(95%CI:87.9%~97.2% ) and 92.6%(95%CI:88.8%~ 96.3% ) in the malignant cases diagnosed from cases with hreast mass by models,respectively.Conclusion So far,the computer diagnostic system based on decision tree has achieved the effectiveness not worse than that of artificial diagnosis under current conditions.Along with the development of relative techniqucs,improvement of diagnostic effectiveness of models will go a long way.

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