Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/101908
Title: | Extended Classification Model of Telemedicine Station |
Author(s): | Tsarov, Roman Tymchenko, Iryna Kumysh, Vladyslav Shulakova, Kateryna Bodnar, Liliia |
Granting Institution: | Hochschule Anhalt |
Issue Date: | 2023 |
Extent: | 1 Online-Ressource (6 Seiten) |
Language: | English |
Abstract: | In the paper the relevance of the scientific problem of creation and development of telemedicine networks and telemedicine stations was proved by a systematic analysis of modern scientific research and regulatory sources. The conducted analysis revealed that there is no unified and system approach in place helping to solve this problem, especially on designing stage and during the technical implementation of these networks and their points. It results in complete or partial incompatibility of existing designs, construction documentation and blueprints as well, which leads to difficulties with various fragments of telemedicine networks and impedes international cooperation in this field. In order to solve this problem the definition of the telemedicine station is given, also its subsystems composition is defined, and an extended telemedicine station classification model is developed in the paper. The proposed classification model is based on the faceted classification method. It allows constructing classes by using any combination of characteristic features of telemedicine stations, while omitting and not using some of the characteristic features. Within the framework of this classification, the intersection of individual classes of telemedicine stations is allowed. A mathematical description of the classification model in the form of a faceted formula is provided. |
URI: | https://opendata.uni-halle.de//handle/1981185920/103859 http://dx.doi.org/10.25673/101908 |
Open Access: | Open access publication |
License: | (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0 |
Appears in Collections: | International Conference on Applied Innovations in IT (ICAIIT) |
Files in This Item:
File | Description | Size | Format | |
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1_6 ICAIIT_2023_paper_6479.pdf | 1.05 MB | Adobe PDF | View/Open |