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Paper   IPM / Cognitive Sciences / 7528
School of Cognitive Sciences
  Title:   Comparison of logistic regression and neural network models in predicting the outcome of biopsy in breast cancer from mammography findings
  Author(s): 
1.  P. Abdolmaleki
2.  M. Gitee
3.  M. Rouhandeh
  Status:   In Proceedings
  Proceeding: International multi Conference in Computer Science and Engineering
  Year:  2003
  Supported by:  IPM
  Abstract:
An Algorithmic model based on the logistic regression analysis and non-algorithmic model based the artificial neural network (ANN) were established. The ability of these models was compared with each other in clinical application to differentiate malignant from benign breast tumors in a study group of 122 patient's records. Each patient's record consisted of 12 subjective features extracted from the conventional mammogram. These findings were encoded as features for an ANN as well as logistic regression model (LRM) to predict the outcome of biopsy. After both models had been trained perfectly on training samples (n-82); the validation samples (n=40) was presented to the trained network as well as the established LRMs. Finally, the diagnostic performance of models was compared to that of the radiologist in terms of sensitivity, specificity and accuracy using receiver operating characteristic (78


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