An ontology-based approach to the analysis of the acid-base state of patients at operative measures

Man Tianxing; Mikhail Lushnov; Dmitry I Ignatov; Yulia Alexandrovna Shichkina; Natalia Alexandrovna Zhukova; Alexander Ivanovich Vodyaho

doi:10.7717/peerj-cs.777

An ontology-based approach to the analysis of the acid-base state of patients at operative measures

PeerJ Comput Sci. 2021 Dec 9:7:e777. doi: 10.7717/peerj-cs.777. eCollection 2021.

Authors

Man Tianxing¹, Mikhail Lushnov², Dmitry I Ignatov³, Yulia Alexandrovna Shichkina⁴, Natalia Alexandrovna Zhukova^{4

5}, Alexander Ivanovich Vodyaho⁴

Affiliations

¹ ITMO University, Saint Petersburg, Russia.
² Almazov National Medical Research Centre, Saint. Petersburg, Russia.
³ National Research University Higher School of Economics, Moscow, Russia.
⁴ St. Petersburg State Electrotechnical University "LETI", Saint Petersburg, Russia.
⁵ St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Saint Petersburg, Russia.

Abstract

Researchers working in various domains are focusing on extracting information from data sets by data mining techniques. However, data mining is a complicated task, including multiple complex processes, so that it is unfriendly to non-computer researchers. Due to the lack of experience, they cannot design suitable workflows that lead to satisfactory results. This article proposes an ontology-based approach to help users choose appropriate data mining techniques for analyzing domain data. By merging with domain ontology and extracting the corresponding sub-ontology based on the task requirements, an ontology oriented to a specific domain is generated that can be used for algorithm selection. Users can query for suitable algorithms according to the current data characteristics and task requirements step by step. We build a workflow to analyze the Acid-Base State of patients at operative measures based on the proposed approach and obtain appropriate conclusions.

Keywords: Acid-base state; Data mining; Ontology; Semantic meta mining.

Grants and funding

This work was supported by the Ministry of Science and Higher Education of the Russian Federation by the Agreement No 075-15-2020-933 dated 13.11.2020 on the provision of a grant in the form of subsidies from the federal budget for the implementation of state support for the establishment and development of the world-class scientific center “Pavlov cente” This work was also supported by State Research No. 0060-2019-0011. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.