A Supervised ML Applied Classification Model for Brain Tumors MRI

Zhengyu Yu, Qinghu He, Jichang Yang, Min Luo
2022 Frontiers in Pharmacology  
Brain Tumor originates from abnormal cells, which is developed uncontrollably. Magnetic resonance imaging (MRI) is developed to generate high-quality images and provide extensive medical research information. The machine learning algorithms can improve the diagnostic value of MRI to obtain automation and accurate classification of MRI. In this research, we propose a supervised machine learning applied training and testing model to classify and analyze the features of brain tumors MRI in the
more » ... ormance of accuracy, precision, sensitivity and F1 score. The result presents that more than 95% accuracy is obtained in this model. It can be used to classify features more accurate than other existing methods.
doi:10.3389/fphar.2022.884495 pmid:35462901 pmcid:PMC9024329 fatcat:7twpuyowwnfhfefmcybyu6mziu