Establishing a model based on data mining for predicting the recurrence factor of breast cancer

Corresponding author: QIAO Qiong, qiaoqiong13 @126.com

DOI: 10.12201/bmr.202009.00011

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  Abstract: Objective：The purpose of this study was to set up the predicting model for the recurrence factor of breast cancer from the open machine learning database(https://www.openml.org/d/13), to find out the best algorithm and the recurrence factor of breast cancer. Methods：By using the SPSS Modeler(18.0) software to establish the model. After the auto-classifier, picking up the algorithms which were ranked top 5 of total accuracy processed the random sampling ten times. Model performance was evaluated by using areas under the receiver operating characteristic curve(AUC) Results：The results showed that the proper algorithm was an artificial neural network with a multilayer perceptron. The AUC of the training data was 0.869, and the AUC of the testing data was 0.894. The clinical-stage of breast cancer could be the main reason for the recurrence. Conclusion：The best algorithm for the database of breast cancer recurrence’s factor was the artificial neural network, the recurrent factor could be the stage of the breast cancer, and the model could provide support for predicting recurrence in breast cancer.

  Key words: Breast; cancer, Recurrence; factor, Model; prediction, SPSS; Modeler, Artificial; neural network

  Submit time: 23 September 2020

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2020-09-17	bmr.202009.00011V1	Download

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