Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Development of a Depression Ontology as a Necessary Step for the Effective Implementation of IT in Psychopathology. / Semin, Timofei I.
Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials, EDM 2022. IEEE Computer Society, 2022. p. 551-554 (International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM; Vol. 2022-June).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Development of a Depression Ontology as a Necessary Step for the Effective Implementation of IT in Psychopathology
AU - Semin, Timofei I.
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Informational technologies have been used in medicine and biology for decades. Machine learning algorithms have proven effective for the analysis of data of all possible types and disorders diagnoses. Decision-making support systems, which were based on ontologies developed at the turn of the century, have also been widely disseminated. However, in psychopathology the situation is different: only a few attempts to implement the IT are presented and their efficiency remains questionable. Furthermore, in recent years, there has been lower progress in the research of mental disorders, despite the growing role of the latter in modern society. In this article, we try to explore the reasons for mentioned problems. From our point of view, the main cause is the absence of a satisfying formalized representation of mental disorders area. Therefore, we assume that it is necessary to create an ontology of mental disorders as a comprehensive and noncontradictory model and propose our approach to the development of the ontology of a more specialized data domain such as Depression, as an initial step. In the article, we also consider already existing approaches to the formalization of the depression and mental disorders data domains and identified possible perspectives.
AB - Informational technologies have been used in medicine and biology for decades. Machine learning algorithms have proven effective for the analysis of data of all possible types and disorders diagnoses. Decision-making support systems, which were based on ontologies developed at the turn of the century, have also been widely disseminated. However, in psychopathology the situation is different: only a few attempts to implement the IT are presented and their efficiency remains questionable. Furthermore, in recent years, there has been lower progress in the research of mental disorders, despite the growing role of the latter in modern society. In this article, we try to explore the reasons for mentioned problems. From our point of view, the main cause is the absence of a satisfying formalized representation of mental disorders area. Therefore, we assume that it is necessary to create an ontology of mental disorders as a comprehensive and noncontradictory model and propose our approach to the development of the ontology of a more specialized data domain such as Depression, as an initial step. In the article, we also consider already existing approaches to the formalization of the depression and mental disorders data domains and identified possible perspectives.
KW - depression
KW - formalization
KW - mental disorders
KW - ontology
KW - psychopathology
KW - systematization
UR - http://www.scopus.com/inward/record.url?scp=85137372888&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/fa09b60d-c2d7-36ad-9c7c-a8d8dc5cdff1/
U2 - 10.1109/EDM55285.2022.9855169
DO - 10.1109/EDM55285.2022.9855169
M3 - Conference contribution
AN - SCOPUS:85137372888
SN - 9781665498043
T3 - International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM
SP - 551
EP - 554
BT - Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials, EDM 2022
PB - IEEE Computer Society
T2 - 23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022
Y2 - 30 June 2022 through 4 July 2022
ER -
ID: 37124414