Brain Tumor Detection Using Machine Learning with CNN Algorithm

Abstract

Abstract: Brain tumors are a major global health issue, and successful treatment frequently depends on an early and precise diagnosis. Traditional methods of brain tumor detection, such as manual interpretation of medical images, can be timeconsuming and prone to human error. Machine learning techniques have emerged as a promising approach to assist medical professionals in the early detection and classification of brain tumors. This study presents a novel method for brain tumor detection utilizing machine learning algorithms .The dataset used in this research comprises a collection of brain MRI (Magnetic Resonance Imaging)scans from diverse sources, including both tumor and non-tumor cases. We preprocess the data by enhancing image quality and for classification, different machine learning techniques are used, such as random forests, support vector machines (SVMs), and convolutional neural networks (CNNs).