Brain Tumor Detection Using AIML

Computer vision, a subfield of AI, specifically deals with allowing computers to construe and understand visual information from the world, often through digital images or videos. It is also very helpful in the healthcare because it detects the diseases through digital images. It involves developing algorithms and models that can recognize objects, patterns, and features within images, allowing machines to observe and extract meaningful information from visual data. "Deep learning is a method in artificial intelligence (AI) that teaches computers to process data in a way that is inspired by the human brain". Deep learning produces outstanding results in a range of fields, including biomedicine, education, and the detection of financial fraud, among others, due to its ability to handle vast volumes of data sets. It has proven to operate admirably and has the ability to use MRI scans to detect brain cancers for precise prognosis. This research project's main objective is to give a thorough summary of the studies and judgements made recently on the identification and classification of brain cancers using MRI scans. The first step in the classification and diagnosis of brain tumors is a rapid review of previous research publications using artificial intelligence and machine learning. The conclusions offered in this paper will provide researchers with a thorough comparison of recent studies as well as a novel viewpoint on the effectiveness of various AIML and Deep Learning approaches. With an emphasis on AI/ML and deep learning techniques, the major objective of this research project is to present a comprehensive overview of recent studies and findings addressing the detection and classification of brain tumors using MRI data. An review of past studies in the field, including the most recent advancements in AI and deep learning, is provided at the outset of this study.