The healthcare sector is a top priority, with end-users expecting the highest standards of patient care, services, and monitoring, regardless of cost. However, despite consuming a substantial portion of both international and national budgets, it often falls short of societal expectations. Medical experts rely on various medical images to diagnose diseases, but patient variability and differences in imaging modalities complicate the process. Additionally, heavy workloads lead to expert fatigue, increasing the risk of errors and inconsistent diagnoses. To address these challenges, an automatic solution is needed. Such a system could diagnose diseases, measure predictive targets, monitor lesions, and provide realistic predictive models, thereby assisting medical experts in efficiently developing treatment plans. Most disease diagnosis methods rely on sound or image analysis, with sound-based diagnoses providing preliminary insights and detailed examinations depending primarily on visual observations.