Identification of Malignant Cells Using Convolutional Neural Network
Rekha Sahu, Akshaya Kumar Dash · 2023
Breast cancer has a high impact as a leading cause of death. Doctors face problems with the quick diagnosis of malignant tumors, which would help in the prevention of cancer at an early stage. Automatic detection of malignant cells is a life-saving boon. The deep learning approach extensively manipulates the data non-linearly to obtain suitable information. In this study, a one-dimensional convolutional neural network is implemented on a tumor dataset to detect malignant and benign tumors. The deep learning approach has achieved 99.9% classification accuracy with 45 epochs and 98.8% ROC-AUC. More experiments are needed on new tumor datasets to study the performance of the one-dimensional convolutional neural network approach in identifying malignant cells.