Abstract
This example outlines the procedures we used to analyze the data for 11,569 pediatric patients at the Loma Linda Hospitals. These children were admitted between January 1, 2009, and December 31, 2015 with a diagnosis of disseminated intravascular coagulation. We attempted to develop a prediction model for survival or death, given the measurements of various tests upon admission. We wanted to see if we could determine a smaller number of lab tests (variables) to predict survival or death. This example goes through the processes used to analyze the data. In the original study in 2018, Linda Miner analyzed the data, Dr. Chandnani wrote up the findings for her residency program research requirements, and Dr. Chandnani was supervised by Drs. Tinsley and Goldstein for the final papers of Dr. Chandnani. Dr. Khichi was instrumental in the first project and provided valuable insights as the team wrote back and forth. For this second edition, Linda Miner wrote this chapter explaining the statistical analyses of the study.
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CITATION STYLE
Miner, L. A., Chandnani, H., Goldstein, M., Khichi, M. H., & Tinsley, C. H. (2023). Disseminated intravascular coagulation predictive analytics with pediatric ICU admissions. In Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition (pp. 375–389). Elsevier. https://doi.org/10.1016/B978-0-323-95274-3.00024-5
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