Diagnosis of Ovarian Cancer Using Convolutional Neural Network and Attention Mechanism

The detection of ovarian cancer at an early stage is pivotal for treating the patient. The process of identifying malignant cells in the ovary is strenuous. Therefore, a proper method is necessary to avoid false positives for efficient treatment. Here, this study has integrated attention mechanism with CNN which are popular deep learning techniques to focus on certain areas of the cell using custom weight range. Furthermore, the model prioritizes crucial features by assigning more weights and put aside insignificant features. The combination of attention mechanism and CNN have propelled the accuracy and efficiency compared to other traditional techniques from IEEE dataset. This research shows that deep learning techniques can offer good odds for the diagnosis of ovarian cancer at an early stage.