The Potential of Machine Learning for Clinical Predictive Analytics

Primitive data analysis is the process of analyzing the data with human expertise and experience. This chapter discusses the shortcomings of primitive data analytics in the healthcare sector due to large data being generated every day. Big data can benefit healthcare in various ways like data management, data analysis, prediction analysis, and electronic reports, and it also helps to find and recognize the target group. Big data helps to identify frauds in healthcare. Big Data increases the hazards to patient data for two reasons. The first is the risk posed by the information itself. The second concern is the peril of big data technologies. Machine learning (ML) algorithms have proved to be of vital importance in almost all walks of life. Based on the types of learning, ML algorithms can be classified into the following categories: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.