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Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring

Infectious diseases accompanied mankind throughout its existence. However, in the 20(th) century, with the implementation od mass vaccination, this problem was partially forgotten. It reappeared at the end of the 2019 with the COVID-19 pandemic. The diseases are associated with high mortality, the m...

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Autores principales: Hajder, Miroslaw, Hajder, Piotr, Gil, Tomasz, Krzywda, Maciej, Kolbusz, Janusz, Liput, Mateusz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486225/
https://www.ncbi.nlm.nih.gov/pubmed/34630754
http://dx.doi.org/10.1016/j.procs.2021.09.145
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author Hajder, Miroslaw
Hajder, Piotr
Gil, Tomasz
Krzywda, Maciej
Kolbusz, Janusz
Liput, Mateusz
author_facet Hajder, Miroslaw
Hajder, Piotr
Gil, Tomasz
Krzywda, Maciej
Kolbusz, Janusz
Liput, Mateusz
author_sort Hajder, Miroslaw
collection PubMed
description Infectious diseases accompanied mankind throughout its existence. However, in the 20(th) century, with the implementation od mass vaccination, this problem was partially forgotten. It reappeared at the end of the 2019 with the COVID-19 pandemic. The diseases are associated with high mortality, the main causes of which are: respiratory failure, acute respiratory distress syndrome, thrombotic complications, etc. As many centuries ago, the key to fighting a pandemic is to diagnose patients with infections as quickly as possible, isolate them, and implement treatment procedures. In this paper we propose a Platform supporting medics in the fight against epidemic. Unlike alternative systems, the proposed IT Platform will ultimately cover all areas of fighting against COVID-19, from the diagnosis of infection, through treatment, to rehabilitation of post-disease complications. Like most clinical information systems, the Platform is based on Artificial Intelligence, in particular Federated Learning. Also, unlike known solutions, it uses all available historical data of the patient’s health and information from real-time mobile diagnostics, using cellular communication and Internet of Things solutions. Such solutions could be helpful in fighting against any future mass infections.
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spelling pubmed-84862252021-10-04 Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring Hajder, Miroslaw Hajder, Piotr Gil, Tomasz Krzywda, Maciej Kolbusz, Janusz Liput, Mateusz Procedia Comput Sci Article Infectious diseases accompanied mankind throughout its existence. However, in the 20(th) century, with the implementation od mass vaccination, this problem was partially forgotten. It reappeared at the end of the 2019 with the COVID-19 pandemic. The diseases are associated with high mortality, the main causes of which are: respiratory failure, acute respiratory distress syndrome, thrombotic complications, etc. As many centuries ago, the key to fighting a pandemic is to diagnose patients with infections as quickly as possible, isolate them, and implement treatment procedures. In this paper we propose a Platform supporting medics in the fight against epidemic. Unlike alternative systems, the proposed IT Platform will ultimately cover all areas of fighting against COVID-19, from the diagnosis of infection, through treatment, to rehabilitation of post-disease complications. Like most clinical information systems, the Platform is based on Artificial Intelligence, in particular Federated Learning. Also, unlike known solutions, it uses all available historical data of the patient’s health and information from real-time mobile diagnostics, using cellular communication and Internet of Things solutions. Such solutions could be helpful in fighting against any future mass infections. The Author(s). Published by Elsevier B.V. 2021 2021-10-01 /pmc/articles/PMC8486225/ /pubmed/34630754 http://dx.doi.org/10.1016/j.procs.2021.09.145 Text en © 2021 The Author(s). Published by Elsevier B.V. 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
Hajder, Miroslaw
Hajder, Piotr
Gil, Tomasz
Krzywda, Maciej
Kolbusz, Janusz
Liput, Mateusz
Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title_full Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title_fullStr Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title_full_unstemmed Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title_short Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
title_sort architecture and organization of a platform for diagnostics, therapy and post-covid complications using ai and mobile monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486225/
https://www.ncbi.nlm.nih.gov/pubmed/34630754
http://dx.doi.org/10.1016/j.procs.2021.09.145
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