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Use of Machine Learning to Diagnose Benign and Malignant Breast Tissues with the Best Degree of Accuracy and in the Shortest Amount of Time

Seyed Matin Malakouti

A tumor is an abnormal lump or growth of cells. Sometimes a tumor is made up of cells that aren't a threat to invade other tissues, this is considered benign. When the cells are abnormal and can grow uncontrollably and spread to other body parts, they are cancerous cells that mean the tumor is malignant. This spreading process is called metastasis. If the cells are not cancerous, the tumor is benign. A benign tumor is less problematic. Doctors may need to remove benign tumors through surgery. These tumors can grow very large, sometimes weighing pounds. They can also be dangerous. They can press on vital organs or block channels. Some benign tumors, such as intestinal polyps, are considered precancerous. They are removed to prevent them from becoming malignant. Benign tumors usually don't come back once removed. But if they do, they return to the same place. In this research, using the features recorded for tumor tissues such as mean radius and mean texture and other available features that are fully mentioned in the article, with the help of Light Gradient Boosting Machine (LGBM), random forest, extra tree, ada boost, and the ensemble method classified benign and malignant tumors with perfect accuracy.