Saeedeh Pourahmad, Mohsen Azad, Shahram Paydar and Hamid Reza Abbasi, Shiraz University of Medical Sciences, Iran

In the present study, the abilities of three classification methods of data mining namely artificial neural networks with feed-forward back propagation algorithm, J48 decision tree method and logistic regression analysis are compared in a medical real dataset. The prediction of malignancy in suspected thyroid tumour patients is the objective of the study. The accuracy of the correct predictions (the minimum error rate), the amount of time consuming in the modelling process and the interpretability and simplicity of the results for clinical experts are the factors considered to choose the best method.

Data Mining, Artificial Neural Networks, Decision Trees, Logistic Regression Analysis, Malignancy, Thyroid Tumour Patients