Machine Learning Techniques for Brain Tumor Detection: A Comparative Analysis

Brain tumors are proliferations of cells originating in the brain, and it typically results from DNA damage. There are over 10 billion active cells in the human brain. Brain cells that have been injured are able to diagnose themselves by dividing to create new cells. Brain tumors are the most deadly disease that cannot be healed when they are advanced. As a result, MRI should be used to identify it early (Magnetic Resonance Image). Therefore, in order for the patient to survive, further alterations will be made. For MRI, grayscale pictures were utilized to detect tumors. With the aid of machine learning methods, we suggested a model for tumor detection. To locate the brain tumor, we employed various ML methodologies. This study’s major goal is to rate the models’ accuracy, precision value, specificity, F1-score, and recall value, using these performance metrics, the optimal model will be anticipated.