Healthcare Data Analytics Using Swarm Intelligence Techniques

Abstract

The healthcare domain plays a significant role. Healthcare information contains heterogeneous data where it has been utilized to mine data in order to provide accurate and optimized results to the user. Hence, the data mining can open up a world of possibilities in terms of diagnosis, prognosis, and therapy. It holds an important place in the medicinal field for the purpose of analyzing huge volumes of data for extracting the salient parts for evaluating the patients' reports. The swarm intelligence (SI) technique has also been utilized for disease diagnosis and treatment. This chapter explains the importance of swarm intelligence technique under data mining in healthcare. It also focused on explaining different algorithms of SI such as particle swarm optimization (PSO) and ant colony optimization (ACO). It also explains its performance and accuracy in delivering the optimized results to the users/patients.