Modeling of survival time of oral squamous cell carcinomas (OSCC) in Hospital Universiti SainsMalaysia using multilayer feedforward neural network

The oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity with up to 50% of the mortality rate. It has been reported about 14.1 million new cancer cases and 8.2 million cancer deaths in 2012. Numbers of studies have been performed to investigate the factors that have direct and indirect or both associated with the OSCC, including their survival time. In this paper, the potential clinic pathological prognostic factors will be determined in patients who attended Hospital Universiti Sains Malaysia (USM) from 2005 to 2015 using multilayer feed-forward (MLFF) neural network. The objective of the current study is to develop a multilayer feed-forward (MLFF) neural network model of time survival of OSCC. Alcohol, tumor site, tumor size and betel quid were significant. These four variables were used to develop the best (MLFF) neural network model of OSCC.