Evaluation of Big Data Analytics and Cognitive Computing in Smart Health Systems

Abstract

The current era of Big Data has led to the use of advanced AI programs that can learn from individual data points, providing intelligent feedback in real time. Their ability to learn and grow more complex is particularly important when they are applied to smart health systems. These systems carry out an analysis of patient data through the use of machine learning and deep learning methods with customizable models designed using the latest advancements in artificial intelligence software. Furthermore, Big Data Analytics has also allowed for a new form of computational intelligence, which is cognitive computing. Experimental results: the average query performance acceleration ratio of the designed complex network big data overlapping information detection method and the other two detection methods is 11.585, 17.411 and 17.642, which proves that the detection method integrates the advantages of cloud computing platform has a higher performance.