CovidStopHospital: e-Health Service for X-Ray-Based COVID-19 Classification and Radiologist-Assisted Dataset Creation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU150169" target="_blank" >RIV/00216305:26220/23:PU150169 - isvavai.cz</a>

Alternative codes found

RIV/00098892:_____/23:10158534

Result on the web

<a href="https://ieeexplore.ieee.org/abstract/document/10333292" target="_blank" >https://ieeexplore.ieee.org/abstract/document/10333292</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

CovidStopHospital: e-Health Service for X-Ray-Based COVID-19 Classification and Radiologist-Assisted Dataset Creation

Original language description

Image data processing using artificial intelligence (AI) algorithms has various applications, including medicine. During the SARS-CoV-2 pandemic, many successful COVID-19 classification algorithms were trained. However, to be effectively used in clinical settings, these algorithms need to be deployed in hospitals. Existing platforms for AI algorithm deployment may not be usable in hospitals that rely on proprietary information systems lacking application interfaces. This paper introduces an easily modifiable general AI-X-ray service capable of deploying AI algorithms even in hospitals using proprietary information systems lacking application interfaces. The CovidStopHospital service, based on the AI-X-ray architecture, is also presented. It is designed for COVID-19 classification and can seamlessly incorporate any classification AI algorithm; the presented solution uses DeepCovid-XR algorithm. The service also includes functionality for radiologists to label X-ray images, facilitating the creation of new datasets. CovidStopHospital underwent testing to ensure its stability and performance, with an average X-ray analysis time of 11.53 seconds and a maximum of 14.01 seconds. The tool can potentially be a valuable diagnostic support tool and is currently in experimental deployment at the University Hospital of Olomouc

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20203 - Telecommunications

Project

<a href="/en/project/VK01010153" target="_blank" >VK01010153: Development of artificial intelligence for multimodal non-destructive forensic material analysis system</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

ISBN

979-8-3503-9328-6

ISSN

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e-ISSN

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Number of pages

6

Pages from-to

62-67

Publisher name

Neuveden

Place of publication

Ghent

Event location

Gent, Belgium

Event date

Oct 30, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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