Recent Advancement in Brain Tumor Detection Using Machine Learning Algorithm: Systematic Survey, Comparisons and Challenges

Abstract

Brain tumors and cancers are fatal diseases that are often caused by the accumulation of genetic diseases and various pathological changes. Cancer cells are abnormal areas that often grow in any life-threatening part of the human body. Cancer, also called a tumor, needs to be identified quickly and accurately in its early stages to see what benefits its cure. Even if modalities have different considerations. Complicated medical history, inadequate diagnosis and treatment, leading causes of death. The purpose of this study is to analyze, review, classify, and address current developments in brain tumor detection using machine learning techniques and supervised, unsupervised, and deep-his learning techniques. Multiple state-of-the-art techniques are grouped into the same cluster, and the results are compared to benchmark datasets for accuracy, sensitivity, specificity, and false-positive metrics. Finally, challenges for future work are also identified.