Brain Tumor Classification Based on Deep Learning Algorithms: A Systematic Literature Review

Along with the times, the medical field has changed and developed with the help of technology that is very helpful and makes it easier for both medical personnel and patients. The application of Artificial Intelligence (AI) also helps in the medical field, especially in medical imaging of Magnetic Resonance Imaging (MRI) images in the diagnosis of brain tumors, but in practice, there have been quite a number of studies trying to apply the application of AI to the diagnosis of brain tumors with results which is quite good with a variety of approaches to Deep Learning methods. Therefore, this is a challenge for the authors and this study aims to apply the right and best deep learning method to produce a higher quality brain tumor classification than previous studies so that the diagnosis of brain tumor disease in patients can improve even better. To identifying and extracting relevant and important data from recent studies, we conducted a systematic literature review using the PRISMA 2020 guidelines. The comparative analysis of recent studies correlated with brain tumor classification using deep learning techniques is considered in this systematic literature review. The outcome of this paper states the various research gaps identified from the systematic literature review.