GUI BASED PREDICTION OF BREAST CANCER STAGES USING ENSEMBLE LEARNING METHOD - S VISHNU VARDHAN REDDY, V NITHISH KUMAR, S USHASUKHANYA (International Journal of Advanced Science and Technology, 2020)
Breast cancer (BC) is one of the most prevalent forms of cancer among women all over the world,accounting for the series of new infections and tumor-related deaths according to statistical data.Machine learning has indeed been commonly used in the identification of benign and cancerous cells ofvarious diseases and has produced successful results. Our research provides a comprehensive guide forthe sensitivity analysis of model output parameters in breast cancer detection. It is important to have anearly diagnosis of cancer. The survey collected through an intrusive procedure can be convenientlydigitalized and treated depending on simulation. With machine learning techniques for medical imagingthe processing speed can improve considerably and treatment can be considerably less expensive on alarge scale. Data processing by a supervised learning method can be carried out with the processes likefeature detection, uni-variate analysis, and bi-variate and multivariate analysis, etc. The main goal is todetect breast cancer phases in clients by machine learning systems. In fact, the assessment rating studydescribes the results one by one from data set of the medical centre and defines the uncertainty index.Recognition, cleaning / preparation of data and simulation of data will be performed on the whole set ofdata. The goal to categorize target data and the outcome thus reveals that the performance of thesuggested machine learning system can be correlated with the best possible precision, exactness, retrievaland F1 ranking.[3]