The Application of Spark in Medical Multidimensional Data Visualization and Statistical Analysis
Haijing Tang, Yangdong Zhou, Taoyi Wang, Yongcan Shi · 2018
With the increasing size, complexity and multidimensionality of medical research data, traditional statistical methods are becoming more and more difficult in analysis. Visualization can present data in an intuitive, visual, and easy-to-read format, which helps medical researchers understand data, and discover scientific views from the interpretation of data. At the same time, as a new parallel computing model, spark technology can also greatly improve the efficiency of the operation. In this article, we explored the application of data visualization methods and spark technology in the study of medical multidimensional data, and developed a visualization scientific discovery platform named datasparking for medical multidimensional data. The platform integrates the functions of interactive chart analysis and statistical analysis methods. It can complete the display of medical multi-dimensional data and analysis of statistical methods, and has the ability to conduct exploratory analysis of medical data. Also, the platform is implemented with Spark as the bottom layer, which improves the efficiency of statistical methods and visualization.