Hybrid Machine Learning Model with Textural Feature Analysis for Brain Tumour Detection

The human brain is an extremely complicated organ that has billions of neurons and cells., each of which is responsible for a specific function. To ensure that the body works perfectly., cells in different tissues are constantly regenerated. Brain tumors can be benign or malignant and they are defined as the abnormal growth of cells in the brain. Tumors., although the abnormality., typically have no effect on the surrounding healthy tissue. Nevertheless., the more aggressive and malignant types., which are brain cancers., have the ability to develop quickly and migrate to other parts of the body. The Voting Classifier suggested in this study is proposed as a method of detection of brain tumors. The classifier illustrated a successful performance., attaining an 89.35% accuracy., a 73.33% precision., and a 94.8% recall. Brain tissue mass lesions diagnosis results indicate that the suggested technique is capable of differentiating brain tumors with a high recall rate., hence., demonstrating a high level of sensitivity in differentiating the true positive cases.