Survey on Big Data Analytics in Health Care

Abstract

Massive amount of data in different forms need to be handled in any healthcare applications. Type of data, size of data, data security and other features has more significance in handling the data. The term big data refers to data with certain characteristics, volume, velocity, value, veracity and variability. Such big data need to be stored, processed, and analyzed for required results. Medical data has more complexity in predicting the results from it, which will have more significance in patient's treatment. Because of its significance, there is need of developing efficient and better performing algorithms, techniques and tools to analyze medical big data. Whereas, the traditional algorithms are not capable for analyzing such complex data. Machine learning algorithms well fit for these kinds of data and analytics. In this Keywords: Big data, Health care, disease prediction, SVM, CNN survey paper, we discussed about characteristic of big data, features of big data, how to represent big data, different types of machine learning algorithms used in big data analytics. We discussed about big data analytics in major healthcare areas like EHR maintenance, disease diagnose, prediction of emergency condition of patients, etc.,. Also stated different machine algorithms usage in disease diagnose and patient's data analysis and discussed about importance of various machine learning algorithms. Here, we have highlighted the areas where big data analytics have been applied in healthcare sectors. It describes the characteristics and features of big data, importance of big data analytics in healthcare sectors, various machine learning algorithms used in big data analytics and their efficiency.