A Comprehensive Review Study on: Optimized Data Mining, Machine Learning and Deep Learning Techniques for Breast Cancer Prediction in Big Data Context

Abstract

In recent years, big data in health care is commonly used for the prediction of diseases. The most common cancer is breast cancer infections of metropolitan Indian women as well as in women worldwide with a broadly factor occurrence among nations and regions. According to WHO, among 14% of all cancer tumours in women breast cancer is well-known cancer in women in India also. Few researches have been done on breast cancer prediction on Big data. Big data is now triggering a revolution in healthcare, resulting in better and more optimized outcomes. Rapid technological advancements have increased data generation; EHR (Electronic Health Record) systems produce a massive amount of patient-level data. In the healthcare industry, applications of big data will help to improve outcomes. However, the traditional prediction models have less efficiency in terms of accuracy and error rate. This review article is about the comparative assessment of complex data mining, machine learning, deep learning models used for identifying breast cancer because accuracy rate of any particular algorithm depends on various factors such as implementation framework, datasets(small or large),types of dataset used(attribute based or image based)etc. Aim of this review article is to help to choose the appropriate breast cancer prediction techniques specifically in the Big data environment to produce effective and efficient result, Because “Early detection is the key to prevention-in case of any cancer”.