Breast cancer is a disease in which malignant (cancer) cells form in the tissues of the breast. It can happen to both the genders (Male & Female). According to the World Health Organization(WHO), breast cancer is the most common cancer among women worldwide, claiming the lives of hundreds of thousands of women each year and affecting countries at all levels of modernization. Breast cancer can be diagnosed through multiple tests, including a mammogram (X-ray), ultrasound, MRI and biopsy. This paper does a comparative study to classify the patient as a PCR or a Non-PCR responder to Neoadjuvant Chemotherapy using various Machine Learning Algorithms such as Neural Network, Principal Component Analysis (PCA ) , Clustering , Predefined Models etc & compares the accuracy of those algorithms.
We further deployed the best accuracy model on a Flask Application