CNN Shines in Brain Tumor Detection: Insights from Deep Learning

The study focuses on the application of deep learning models for the detection and classification of brain tumors, a critical area in healthcare. Brain tumors, among various central nervous system disorders, pose significant challenges in terms of detection and treatment. The research reviews several deep learning models’ performance in this context. Notably, a Convolutional Neural Network (CNN) achieved exceptional results with an accuracy of 93.5%, an AUC of 98.57%, a recall rate of 91.7%, and a loss of 0.260. This CNN outperformed other models and exhibited a balanced accuracy curve during training. These findings underscore the immense potential of deep learning models, especially CNNs, in precise brain tumor identification. These models hold promise for improving the diagnosis and treatment of brain-related disorders, offering valuable contributions to the field of healthcare.