Breast Cancer Detection using Machine Learning Algorithms
Prerita, Nidhi Sindhwani, Ajay Rana, Alka Chaudhary
Abstract
Breast cancer is diagnosed in over 2 million people worldwide each year., according to cancer research. accounting for the majority of all cancer diagnoses and deaths., rendering it a major public health issue. However, in its early stages, it is still a curable cancer. Early detection of breast cancer, combined with prompt and effective treatment, improves patients' prognosis and recovery. There is a high risk of confusion and incorrect detection when classifying tumors, which must be addressed. Unnecessary therapies can be avoided if patients are correctly classified. This research is focused on machine learning (ML) algorithms, with the aim of reviewing a python methodology and its use in cancer diagnosis and prognosis through the development of a basic machine learning model. Machine learning has a distinct benefit, It is capable of distinguishing important characteristics in large datasets of breast cancer. The method is commonly used in pattern recognition and prediction modelling.