Abstract

Breast cancer is one of the second leading causes of cancer death in women.\nDespite the fact that cancer is preventable and curable in primary stages, a huge number of\npatients are diagnosed with cancer very late. Conventional methods of detecting and\ndiagnosing cancer mainly depend on skilled physicians, with the help of medical imaging, to\ndetect certain symptoms that usually appear in the later stages of cancer. Therefore, we present\nhere the computerized method for cancer detection in its early stage within a very short time.\nHere, we have used Machine learning to train a model using the predicted features of the\nnuclei of cells. A comparative study of two different algorithms KNN and SVM is conducted\nwhere the accuracy of each classifier is measured. After this, we analyze a digital image of a\nfine needle aspirate (FNA) of breast tissue using image processing to find out the features of\nnuclei of the cells. We then apply the feature values to our trained model to find whether the\ntumor developed is benign or malignant.