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Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective

The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, w...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848050/
https://www.ncbi.nlm.nih.gov/pubmed/27170907
http://dx.doi.org/10.1109/JTEHM.2015.2485268
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description The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children’s Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children’s Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto.
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spelling pubmed-48480502016-05-11 Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective IEEE J Transl Eng Health Med Article The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children’s Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children’s Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto. IEEE 2015-10-01 /pmc/articles/PMC4848050/ /pubmed/27170907 http://dx.doi.org/10.1109/JTEHM.2015.2485268 Text en 2168-2372 © 2015 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
spellingShingle Article
Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title_full Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title_fullStr Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title_full_unstemmed Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title_short Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective
title_sort health informatics for neonatal intensive care units: an analytical modeling perspective
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848050/
https://www.ncbi.nlm.nih.gov/pubmed/27170907
http://dx.doi.org/10.1109/JTEHM.2015.2485268
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