Enhanced Brain and Lung Tumor Detection by Explainable AI Techniques

Cancer accounts for most deaths worldwide, and cases of brain and lung tumors are emerging at a rapid pace.Early detection is of prime importance for better patient outcomes, but the conventional methods of diagnosing cancer rely upon MRI scans, and they are timeconsuming, two-dimensional, and a potential source of inaccuracies.In India alone, more than 70,000 cases are reported of lung cancer.About 50,000 individuals have brain tumors.This research uses deep learning models-sequential model and the pre-trained VGG-16 model-to provide accurate classification for brain and lung tumors from MRI and CT images.With a combination of machine learning and image processing, the automated system reduces false negatives and false positives, thereby attaining high accuracy in diagnosis.Additionally, the use of Explainable AI (XAI) techniques improves the interpretation of predictions by healthcare professionals.These advanced, automated solutions are thus directed toward enhanced early cancer detection in the pursuit of better patient outcomes.