Brain Tumor Prediction from EEG Signal using Machine Learning Algorithm

Abstract

Brain tumors are a type of cancerous growth that occurs in the brain tissue. It can develop in any part of the brain and can be either malignant or benign. Brain tumors can cause a range of symptoms such as headaches. seizures. difficulty speaking, vision problems, and cognitive impairment [1]. An early and precise diagnosis of a brain tumor is crucial for the effective administration of the remedy. Brain tumors can start outside the brain and spread there, or it can start inside the brain and grow there. Headaches, nausea, and balance issues are some of the indications and symptoms that the tumor can produce as it spreads because it puts pressure on the surrounding brain tissue and alters how it functions. Early tumor detection minimizes the need for surgery and other forms of treatment, improving the prognosis for many patients. The development of new technologies that improve neurosurgery’s success rate and avoid problems is still ongoing today. Magnetic resonance imaging (MRr) is one of the most often utilized procedures for analyzing pictures of brain tumors [6]. EEG signal is used in the suggested method to forecast brain tumors. SVM is used by this system to forecast brain tumors. When compared to other methods, the accuracy rate of the SVM (support vector machine) approach was shown to be higher.