Design Simulation and Assessment of Prediction of Mortality in Intensive Care Unit Using Intelligent Algorithms
Big data in healthcare refers to vast amounts of data generated by the adoption of digital technology that collect patient records and aid in the management of hospital performance, which would otherwise be too large and complex for traditional technologies. We have chosen Mortality Prediction in Hospital ICU for this paper. In recent years, there has been a determined push in hospitals to implement digital health record systems. Between 2008 and 2014, the number of non-federal acute care hospitals in the United States using basic digital systems climbed from 9.4 percent to 75.5 percent. In the near future, the percentage increase in the hospital's digital information will be enormous, and we will need to apply modern big data techniques to analyse those datasets. In the best sense, the future of medical diagnosis and therapy is a combination of medical judgement and an algorithmic diagnostic tool based on large medical information. For our research, we used the MIMIC III database. In this paper, we will go over why Mortality Prediction in ICU is interesting, as well as the method we used to examine and address the problem.