Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102668
Title: Entropy-probabilistic modeling as a tool for forming key competencies of a doctor
Authors: Tyrsin, A. N.
Yashin, D. A.
Surina, A. A.
Issue Date: 2020
Publisher: IOP Publishing Ltd
Citation: Tyrsin A. N. Entropy-probabilistic modeling as a tool for forming key competencies of a doctor / A. N. Tyrsin, D. A. Yashin, A. A. Surina. — DOI 10.1088/1742-6596/1691/1/012162 // Journal of Physics: Conference Series. — 2020. — Vol. 1691. — Iss. 1. — 012162.
Abstract: The possibility of using modern digital educational technologies in the formation of key competencies of a doctor is shown on the example of the entropy-probability model, which is a synthesis of the system-entropy approach and multidimensional risk analysis of stochastic systems. Examples of practical application of this model in preventive medicine are given: Analysis of population entropy in the prevention of noncommunicable diseases, comprehensive assessment of the effectiveness and safety of medicines, quantitative assessment of population health with the determination of the contribution of individual risk factors, and systematic analysis of population changes in monitoring risk factors. The introduction of entropy-probabilistic modeling in the educational process will help in the formation of the doctor's basic universal, professional competencies and systematic clinical thinking. © Published under licence by IOP Publishing Ltd.
Keywords: E-LEARNING
ENTROPY
HEALTH RISKS
RISK ANALYSIS
STOCHASTIC MODELS
STOCHASTIC SYSTEMS
COMPREHENSIVE ASSESSMENT
NON-COMMUNICABLE DISEASE
PREVENTIVE MEDICINES
PROBABILISTIC MODELING
PROBABILITY MODELING
PROFESSIONAL COMPETENCIES
QUANTITATIVE ASSESSMENTS
SYSTEMATIC ANALYSIS
RISK ASSESSMENT
URI: http://hdl.handle.net/10995/102668
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85098061504
PURE ID: 20383600
5201c6bb-bed3-428e-9eeb-3d45f7dc6144
ISSN: 17426588
DOI: 10.1088/1742-6596/1691/1/012162
metadata.dc.description.sponsorship: The work was supported by the RFBR (grant 20-51-00001 Bel_a).
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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