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Respiratory decision support systems

Computerized decision support systems help both health professionals and patients make the right diagnostic and therapeutic decisions in a timely fashion, capitalizing on the available knowledge as well as on data-driven methods. The wealth of data, which have been made available via connected healt...

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Detalles Bibliográficos
Autores principales: Chouvarda, Ioanna, Perantoni, Eleni, Steiropoulos, Paschalis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245527/
http://dx.doi.org/10.1016/B978-0-12-823447-1.00008-7
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author Chouvarda, Ioanna
Perantoni, Eleni
Steiropoulos, Paschalis
author_facet Chouvarda, Ioanna
Perantoni, Eleni
Steiropoulos, Paschalis
author_sort Chouvarda, Ioanna
collection PubMed
description Computerized decision support systems help both health professionals and patients make the right diagnostic and therapeutic decisions in a timely fashion, capitalizing on the available knowledge as well as on data-driven methods. The wealth of data, which have been made available via connected health technologies, the broader uptake of systems biology/medicine, and the technological progress of artificial intelligence are the three pillars leveraging such systems in respiratory care. In addition, for decision support, the following should be considered: (a) the complex interaction of the respiratory system with the circulatory and other systems, (b) the respiratory system decision-making spans in many directions and time scales, in acute and chronic care, and (c) the wealth of informative measurements and signals can contribute in this. This chapter will present methodological analysis for several respiratory disorders, namely sleep apnea, respiratory infections (including the COVID-19 pandemic), chronic lung diseases, and ventilation in respiratory care, including the data and methods applicable in each case.
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spelling pubmed-92455272022-07-01 Respiratory decision support systems Chouvarda, Ioanna Perantoni, Eleni Steiropoulos, Paschalis Wearable Sensing and Intelligent Data Analysis for Respiratory Management Article Computerized decision support systems help both health professionals and patients make the right diagnostic and therapeutic decisions in a timely fashion, capitalizing on the available knowledge as well as on data-driven methods. The wealth of data, which have been made available via connected health technologies, the broader uptake of systems biology/medicine, and the technological progress of artificial intelligence are the three pillars leveraging such systems in respiratory care. In addition, for decision support, the following should be considered: (a) the complex interaction of the respiratory system with the circulatory and other systems, (b) the respiratory system decision-making spans in many directions and time scales, in acute and chronic care, and (c) the wealth of informative measurements and signals can contribute in this. This chapter will present methodological analysis for several respiratory disorders, namely sleep apnea, respiratory infections (including the COVID-19 pandemic), chronic lung diseases, and ventilation in respiratory care, including the data and methods applicable in each case. 2022 2022-06-17 /pmc/articles/PMC9245527/ http://dx.doi.org/10.1016/B978-0-12-823447-1.00008-7 Text en Copyright © 2022 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Chouvarda, Ioanna
Perantoni, Eleni
Steiropoulos, Paschalis
Respiratory decision support systems
title Respiratory decision support systems
title_full Respiratory decision support systems
title_fullStr Respiratory decision support systems
title_full_unstemmed Respiratory decision support systems
title_short Respiratory decision support systems
title_sort respiratory decision support systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245527/
http://dx.doi.org/10.1016/B978-0-12-823447-1.00008-7
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