Detection of Stomach Cancer Using Deep Neural Network in Healthcare Sector

In this paper, we develop a deep learning model using dense neural network (DenseNet) to detect the gastric cancer in stomach region using computerised tomography (CT) imaging. The image is initially pre-processed and the features are extracted, where these features are used for training the DenseNet to develop a model. The model is tested and validated against various stomach cancer datasets to check the efficacy of the model. The simulation is validated in terms of various performance metrics that include accuracy, precision, recall and f-measure. The results show that the proposed method is effective in improving the rate of detection over various CT images than other methods.