C4.5: programs for machine learning
C4.5: programs for machine learning
SPSS for Windows Tables, Release 5
SPSS for Windows Tables, Release 5
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Enhancement of a Chinese discourse marker tagger with C4.5
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Applying text and data mining techniques to forecasting the trend of petitions filed to e-People
Expert Systems with Applications: An International Journal
International Journal of Computational Intelligence Studies
Combining techniques for software quality classification: An integrated decision network approach
Expert Systems with Applications: An International Journal
MicroCBR: A case-based reasoning architecture for the classification of microarray data
Applied Soft Computing
Expert Systems with Applications: An International Journal
Predicting seminal quality with artificial intelligence methods
Expert Systems with Applications: An International Journal
Accurate Prediction of Coronary Artery Disease Using Reliable Diagnosis System
Journal of Medical Systems
Structural and Multidisciplinary Optimization
Hi-index | 12.06 |
Current evidence supports a clear association between clinical and pathologic factors and recurrence-free survival (RFS) in breast cancer patients. The Cox regression model is the most common tool for investigating simultaneously the influence of several factors on the survival time of patients. But it gives no estimate of the degree of separation of the different subgroups. We propose to analyze different decision tree methods (C&RT, CHAID, QUEST, C4.5 and ID3) and use them additionally to the well-known Kaplan-Meier estimates to investigate the predictive power of these methods. Five hundred patients were included to the study. Two hundred and seventy-nine of them had complete data for prognostic factors and median follow-up is about 40.5 months. First, decision tree methods were analyzed for prognostic factors. Then, according to multidimensional scaling method C4.5 (error rate 0.2258 for training set and 0.3259 for cross-validation) performed slightly better than other methods in predicting risk factors for recurrence. Tumor size, age of menarche, hormonal therapy, histological grade and axillary nodal status are found that an important risk factors for the recurrence. Eight terminal nodes were found and stratified by Kaplan-Meier survival curves. Larger tumor size (=4.4cm) and receiving no hormonal therapy in a small subgroup of patients were associated with worse prognosis. The five-year RFS is 71.3% in the whole patient population. The sensitivity, specificity and predictive rates calculated by C4.5 method were found 43.8%, 91% and 77.4%, respectively. In this study, C4.5 showed a better degree of separation. As a result, we recommend to use decision tree methods together with Kaplan-Meier analysis to determine risk factors and effect of this factors on survival.