Explainable AI for Gastrointestinal Disease Detection using Ensemble Deep Learning Techniques

This is a GI disease and a global threat, with treatment that doesn't take long when diseases are rightly identified. This study is introducing a novel approach to use multiple AI deep learning systems, to use for GI diseases identification and to offer explanations. In order to distinguish a few details amid the medical images based on endoscopy images then an identifying framework of such a type of deep learning techniques incorporating CNNs, RNNs, & the transformers. It indicates to doctors which parts of the image are responsible for the most salient results, all while keeping the results in the form of a explainability tools Grad-CAM, SHAP, and LIME. That is all the more true because the system's decision-making process is displayed in a framework and that's how healthcare providers trust AI predictions. That is, clearly predictive properties of the system, confirmed by the test result, accompanied with additional information of interpretative nature that can be utilized by physicians. The system enhances diagnostic processes with minimal error, which indicates that more doctors will trust in artificial intelligence medical solutions.