Breast Tumor Detection Using Classification Algorithm
Keywords:
Malignant, Benign, Diagnosis, Radiologist, Survival, TumorsAbstract
Breast cancer is the most common cancer in women. It is the leading cause of cancer death in developing countries and the second leading cause of cancer death in women in the United States, behind only lung cancer. Females are more likely to develop breast cancer. However, in a few instances, it is clear that males have also been affected. Breast cancer has been discovered. [1] Breast tumors may be either cancerous or non- cancerous. Benign tumors are easily treated with doctor-prescribed medications. Malignant tumors are a sign of a high risk of breast cancer and should be removed as soon as possible. Early identification and treatment of tumor lowers the risk of cancer-related death. The survival rate of breast cancer patients in America has been reported to be 90% in recent years, but it is as low as 60% in India. [2] The key cause of this shortcoming is late tumor diagnosis and classification, which causes treatment delays. Using machine learning to perform a task will reduce the workload of physicians and radiologists. According to research, doctors can only diagnose breast cancer with a 79 percent accuracy rate, while machines can diagnose it with a 91 percent accuracy rate. Early diagnosis is the best way to increase the chance of treatment and chance of survival.
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References
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