Abnormality Classifications Using Machine Learning
Anupam Pratap Singh, Ravendra Singh, Nitin Arora · 2023
The brain can be visualized in painstaking depth using magnetic resonance imaging (MRI), a non-invasive technique that utilizes radio waves and a magnetic field. Early detection of brain tumors is critical for improving survival rates, and machine learning algorithms can play an important role in analyzing MRI images to accurately detect and grade tumors. Extraction of relevant information from MRI scans, such as the shape, size, and texture of various tissue types, is a common method for applying machine learning to detect brain tumors. The support vector machine (SVM) classifier is then trained with these attributes to precisely categorize new images as tumor or non-tumor. Healthcare practitioners can enhance their capacity to identify and treat brain tumors by combining the strength of molecular imaging with algorithms that employ machine learning, which will ultimately enhance patient outcomes.