Predicting patients survival using supervised techniques
Sofianita Mutalib, Nor Aina Azman, Shuzlina Abdul-Rahman · 2011
This paper attempts to predict the survival of patients using supervised machine learning techniques. To predict this task, the variables were identified and retrieved from the StatLib database. Both the artificial neural networks and linear regression models were used to perform the task. Experimental results, based on the classification accuracy were analysed from training and testing datasets. To increase the performance generalisation, data were randomly divided into three different datasets and experimented. Results showed that the artificial neural networks model outperformed the linear regression models in most cases.