Technology has significantly impacted the medical sector, helping to prevent, treat, and monitor a wide range of patient conditions. The medical field has seen several improvements and increased sophistication since the advent of machine learning, deep learning, and artificial intelligence based algorithms and models. Applications for computer-aided diagnosis have automated thousands of medical diseases, and life-saving interventions will inevitably follow suit. The medical community places a great deal of emphasis on the identification and categorization of tumours, which it claims are the main causes of death in all age categories. The manual labor required to gather, record, categorize, and then arrange for an accurate diagnosis is laborious and time-consuming, which increases the possibility of mistakes. With the need of early identification and prompt treatment for patients with various tumor types, the field has welcomed sophisticated, automated solutions that harness the power of artificial intelligence and machine learning algorithms. Modern medical imaging technologies have made brain tumor identification and categorization less complicated, but radiologists and other related medical specialists still have a lot of work ahead of them. Maximum accuracy is used to detection and classification, and special attention is paid to how medicine affects progression or regression. The accuracy of manual detection methods varies with years of expertise and qualifications; hence, there is a growing need for computer-aided diagnosis procedures, which has created new avenues for research and development.