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Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. / Naydanov, Chimit; Palchunov, Dmitriy; Sazonova, Polina.

Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015. Institute of Electrical and Electronics Engineers Inc., 2015. стр. 33-38 7361845 (Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Naydanov, C, Palchunov, D & Sazonova, P 2015, Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. в Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015., 7361845, Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015, Institute of Electrical and Electronics Engineers Inc., стр. 33-38, International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015, Novosibirsk, Российская Федерация, 28.10.2015. https://doi.org/10.1109/SIBIRCON.2015.7361845

APA

Naydanov, C., Palchunov, D., & Sazonova, P. (2015). Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. в Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015 (стр. 33-38). [7361845] (Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON.2015.7361845

Vancouver

Naydanov C, Palchunov D, Sazonova P. Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. в Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015. Institute of Electrical and Electronics Engineers Inc. 2015. стр. 33-38. 7361845. (Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015). doi: 10.1109/SIBIRCON.2015.7361845

Author

Naydanov, Chimit ; Palchunov, Dmitriy ; Sazonova, Polina. / Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015. Institute of Electrical and Electronics Engineers Inc., 2015. стр. 33-38 (Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015).

BibTeX

@inproceedings{de24e10b25014e95a682decf9c4e66c4,
title = "Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records",
abstract = "This paper describes the methods of development of ontologies and ontological models in medicine. A four-level model of knowledge representation is suggested. Algorithms for prevention of critical condition risks and complications are developed on the basis of ontological methods of knowledge representation. The work is based on the model-theoretic approach to representation of medical knowledge. The knowledge is represented through partial atomic diagrams of algebraic systems, as well as representation of patient's case data via Boolean-valued models. Ontology and ontological model of the {"}spinal deformity and degenerative diseases of the spine{"} subject domain have been developed. The ontology model contains: a) universal knowledge that is true for all patients, b) data on specific patients, and c) estimated (fuzzy) knowledge that is used for recommendations for doctors. Estimated knowledge is a set of probabilistic hypotheses on the possibility of emergence of patient's critical condition or complication. An algorithm for generation of estimated (fuzzy) knowledge, based on the analysis of medical records, has been developed. A software system for generating recommendations to prevent and reduce the risk of patient's critical condition has been implemented. The software system has been tested on the data of patients with spinal deformity and degenerative diseases of the spine.",
keywords = "Boolean-valued model, critical conditions, degenerative diseases of the spine, knowledge representation, ontology model, precedent model, risk management, spinal deformity",
author = "Chimit Naydanov and Dmitriy Palchunov and Polina Sazonova",
year = "2015",
month = dec,
day = "21",
doi = "10.1109/SIBIRCON.2015.7361845",
language = "English",
series = "Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "33--38",
booktitle = "Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015",
address = "United States",
note = "International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015 ; Conference date: 28-10-2015 Through 30-10-2015",

}

RIS

TY - GEN

T1 - Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records

AU - Naydanov, Chimit

AU - Palchunov, Dmitriy

AU - Sazonova, Polina

PY - 2015/12/21

Y1 - 2015/12/21

N2 - This paper describes the methods of development of ontologies and ontological models in medicine. A four-level model of knowledge representation is suggested. Algorithms for prevention of critical condition risks and complications are developed on the basis of ontological methods of knowledge representation. The work is based on the model-theoretic approach to representation of medical knowledge. The knowledge is represented through partial atomic diagrams of algebraic systems, as well as representation of patient's case data via Boolean-valued models. Ontology and ontological model of the "spinal deformity and degenerative diseases of the spine" subject domain have been developed. The ontology model contains: a) universal knowledge that is true for all patients, b) data on specific patients, and c) estimated (fuzzy) knowledge that is used for recommendations for doctors. Estimated knowledge is a set of probabilistic hypotheses on the possibility of emergence of patient's critical condition or complication. An algorithm for generation of estimated (fuzzy) knowledge, based on the analysis of medical records, has been developed. A software system for generating recommendations to prevent and reduce the risk of patient's critical condition has been implemented. The software system has been tested on the data of patients with spinal deformity and degenerative diseases of the spine.

AB - This paper describes the methods of development of ontologies and ontological models in medicine. A four-level model of knowledge representation is suggested. Algorithms for prevention of critical condition risks and complications are developed on the basis of ontological methods of knowledge representation. The work is based on the model-theoretic approach to representation of medical knowledge. The knowledge is represented through partial atomic diagrams of algebraic systems, as well as representation of patient's case data via Boolean-valued models. Ontology and ontological model of the "spinal deformity and degenerative diseases of the spine" subject domain have been developed. The ontology model contains: a) universal knowledge that is true for all patients, b) data on specific patients, and c) estimated (fuzzy) knowledge that is used for recommendations for doctors. Estimated knowledge is a set of probabilistic hypotheses on the possibility of emergence of patient's critical condition or complication. An algorithm for generation of estimated (fuzzy) knowledge, based on the analysis of medical records, has been developed. A software system for generating recommendations to prevent and reduce the risk of patient's critical condition has been implemented. The software system has been tested on the data of patients with spinal deformity and degenerative diseases of the spine.

KW - Boolean-valued model

KW - critical conditions

KW - degenerative diseases of the spine

KW - knowledge representation

KW - ontology model

KW - precedent model

KW - risk management

KW - spinal deformity

UR - http://www.scopus.com/inward/record.url?scp=84969262302&partnerID=8YFLogxK

U2 - 10.1109/SIBIRCON.2015.7361845

DO - 10.1109/SIBIRCON.2015.7361845

M3 - Conference contribution

AN - SCOPUS:84969262302

T3 - Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015

SP - 33

EP - 38

BT - Proceedings - 2015 International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - International Conference on Biomedical Engineering and Computational Technologies, SIBIRCON 2015

Y2 - 28 October 2015 through 30 October 2015

ER -

ID: 25329497