Explainable Artificial Intelligence for brain Tumor Detection

As per the growing concern of Brain Tumor diagnosis a model is introduced namely tumor NET XAI, for advantages for enhance efficiency in brain tumor detection this Framework builds on a different data set such as MRI scans which also consists of data cleaning, augmentations and normalization for ensuring quality Normalisation for ensuring quality the ideas about to combining CNNs with random forest for feature extraction and SVM classifiers, models uses IFAV (SHAP, GRAD-CAM and LIME) for understanding it more specifically. It also helps clinicians for better understanding the influences predictions. This approach aims in enhancing to accuracy of Diagnostic field and also clinicians trust in brain tumor detection thoroughly.