ABSTRACT
Cancer is the second cause of death in the world. 8.8 million patients died due to cancer in 2015. Breast cancer is the leading cause of death among women. Several types of research have been done on early detection of breast cancer to start treatment and increase the chance of survival. Most of the studies concentrated on mammogram images. However, mammogram images sometimes have a risk of false detection that may endanger the patient’s health. It is vital to find alternative methods which are easier to implement and work with different data sets, cheaper and safer, that can produce a more reliable prediction. This project we proposes a model of Machine Learning (ML) algorithms including Support Vector Machine (SVM). Here it also detect types of Breast Cancer in different categories like NORM=Normal, CALC=Calcification, CIRC=Circumscribed Masses, SPIC=Speculated Masses, MISC=ill-defined Masses, ARCH=Architectural Distortion, ASYM=Asymmetry.
PROJECT OUTPUT
PROJECT VIDEO
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