Development of a Novel Machine Learning Framework For Brain Tumors Using Explainable Ai And Deep Learning

Majorly in cancers related to Central Nervous System, 85% to 90% of all initial central nervous system (CNS) tumors are brain tumors. Tumors can be detected using multiple state-of-the-art technologies. We studied 6251 MRI scans which contained images for Glioma, Meningioma, Pituitary tumors and no tumor. We built a CNN (Convolutional Neural Networks) model which was iterated for 5 epochs, with overall test accuracy of 83.1%, a training loss of 0.44 and a validation loss of 0.41 for 1200 test images. 225 images were correctly classified as glioma and 195 as meningioma. There are 248 images for no tumor and 342 images for pituitary. 190 images were classified incorrectly. We further used the Explainable AI model LIME to understand the prediction of the CNN model.