Publication

Abstract : In this research, the performance of different deep learning models, including CNN + RNN, VGG16 + RNN, VGG19 + RNN, ResNet50 + RNN, and InceptionV3 + RNN in predicting brain tumour grades by employing Electronic Health Record (EHR) and imaging data are evaluated. Confusion matrices show the models' abilities to predict, showing the results of the prediction capability of each model over tumour grades. From the result and analysis, InceptionV3+RNN is performing better than all other ML models. With the multimodal fusion techniques, an informed decision can be made about the grades of the cancer cells, and the clinicians can give the proper treatment to the patients. The proposed approach can be implemented in real-time to predict the cancer grades with the highest level of accuracy for better treatment.