The impact of Markov model to predict the status of children with congenital heart disease at post-operative ICU-Reference-Cited by-同舟云学术

The impact of Markov model to predict the status of children with congenital heart disease at post-operative ICU

Published:2023-08 Issue:6 Volume:15 Page:3285-3292
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Sharwardy Sharmin Nahar^ORCID,Sarwar Hasan,Rahman Mohammad Zahidur

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01388-3.pdf

Reference36 articles.

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3. Moorman JR, Carlo WA, Kattwinkel J, Schelonka RL, Porcelli PJ, Navarrete CT, Bancalari E, Aschner JL, Walker MW, Perez JA et al (2011) Mortality reduction by heart rate characteristic monitoring in very low birth weight neonates: a randomized trial. J Pediatr 159(6):900–906

4. Ruminski CM, Clark MT, Lake DE, Kitzmiller RR, KeimMalpass J, Robertson MP, Simons TR, Moorman JR, Calland JF (2019) Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit. J Clin Monit Comput 33(4):703–711

5. Spaeder MC, Moorman JR, Tran CA, Keim-Malpass J, Zschaebitz JV, Lake DE, Clark MT (2019) Predictive analytics in the pediatric intensive care unit for early identification of sepsis: capturing the context of age. Pediatr Res 86(5):655–661

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