Predicting the survival in breast cancer using Hidden Markov Model
Abstract
Among the women worldwide breast cancer is one of the widespread killer diseases. Early detection of \nthe disease is important in patient survival. The main objective of this research was to evaluate predictive \nability of hidden markov model in prediction of breast cancer survivability. \nThe breast cancer data set used in this investigation were acquired of Health department of Kerman \nprovince and includes the information of 900 breast cancer patients, aged 15 to 80 years, and its \nassociated risk factors among patients since 1999 to 2007. Hidden markov model was made based on a \nset of 675 patients information (75% of data) and that was validate in a test set of 225 patients \ninformation (25 % of data). The Area Under the ROC Curve (AUC), sensitivity, specificity and \naccuracy used as measures of validate of the efficiency of model. \nThe sensitivity, specificity, accuracy and the area under the ROC curve of the hidden markov model \nwas 0.989, 0.99, 0.939 and 0.94, respectively. According to the four evaluation criteria, hidden markov \nmodel had good performance, therefore hidden markov model and predict the diagnosis of breast cancer is \nrecommended.
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