A survey of big data architectures and machine learning algorithms in healthcare

Abstract

Big Data has gained much attention from researchers in healthcare, bioinformatics, and information sciences. As a result, data production at this stage will be 44 times greater than that in 2009. Hence, the volume, velocity, and variety of data rapidly increase. Hence, it is difficult to store, process and visualise this huge data using traditional technologies. Many organisations such as Twitter, LinkedIn, and Facebook are used big data for different use cases in the social networking domain. Also, implementations of such architectures of the use cases have been published worldwide. However, a conceptual architecture for specific big data application has been limited. The intention of this paper is application-oriented architecture for big data systems, which is based on a study of published big data architectures for specific use cases. This paper also provides an overview of the state-of-the-art machine learning algorithms for processing big data in healthcare and other applications.