Big Medical Data Analytics Using Apache Spark Framework

Big medical data analytics has become an essential research area in the healthcare industry. The vast amount of data generated by various medical devices, clinical systems, and research studies needs to be processed, analyzed and visualized to extract valuable insights. In this paper, we present methods and techniques for processing and analyzing Big medical data using Apache Spark, a widely used big data processing framework. We present three case studies using different types and formats of COVID-19 related data. We evaluate the performance of processing and analytics of these datasets using Apache Spark framework and a cluster of Spark Docker containers. Our experiments demonstrate the feasibility of using Apache Spark for Big medical data analytics.