Architecture and organization of a platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring
| Autor: | Mirosław Hajder, Mateusz Liput, Janusz Kolbusz, T. Gil, Maciej Krzywda, Piotr Hajder |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Coronavirus disease 2019 (COVID-19)
Computer science Medical Platform System COVID-19 Acute respiratory distress medicine.disease Article Federated learning AI-based decision making Cellular communication Pandemic medicine General Earth and Planetary Sciences Mass vaccination Medical emergency Architecture Federated Learning Thrombotic complication General Environmental Science |
| Zdroj: | KES Procedia Computer Science |
| Popis: | Infectious diseases accompanied mankind throughout its existence. However, in the 20th 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. |
| Databáze: | OpenAIRE |
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