Breast Cancer Diagnosis and Prediction Using Machine Learning

Today, one of the most prevalent illnesses affecting women is breast cancer. It is now the second leading cause of cancer-related death in women. There are ۴.۵ to ۵% more new cancer cases yearly, raising the morbidity rate globally. It has been demonstrated that early detection of any cancer when combined with the proper diagnosis and therapy, can increase the patient survival rate. Mammography is used to diagnose breast cancer. Mammograms are produced on film by the radiologist using a machine. The oncologist examines these mammograms and makes a diagnosis for further therapy. Since specialists are not available in all general hospitals, patients have had to wait for their reports. So, waiting for a breast cancer diagnosis could take some time. The patient's chance of survival may be lowered because of cancer spreading due to this delay. Therefore, a computer can identify breast cancer using machine learning to make the process quick and accurate. This does not imply that computers will take the role of experts or doctors, but rather that computers will help experts better analyze cases and deliver outcomes faster. To improve the accuracy and efficiency of cancer prediction, this study summarizes breast cancer diagnosis using machine learning algorithms. The primary goals of the evaluated publications are a reliable diagnosis and classification.

کلیدواژه ها:

Breast Cancer ، Machine Learning ، Prediction ، Diagnosing