350 rub
Journal Biomedical Radioelectronics №3 for 2023 г.
Article in number:
Development of a decision support system for the organization of a medical worker's working time based on artificial intelligence methods
Type of article: scientific article
DOI: https://doi.org/10.18127/j15604136-202303-07
UDC: 684.511
Authors:

S.Yu. Zhuleva1, A.V. Kroshilin2, S.V. Kroshilina3

1–3 Ryazan State Radio Engineering University named after V.F. Utkina (Ryazan, Russia)

Abstract:

The process of forming the workload of medical personnel is characterized by the collection and processing of ambiguous and uncertain information. The existing automated systems do not take into account the incompleteness of information about the process of selection and distribution of working hours of medical workers for a particular healthcare institution.

Purpose – development of an automated system to improve the efficiency of the process of load distribution of medical personnel.

A mathematical model for the organization of a doctor's working time based on fuzzy logic is proposed, which allows taking into account the totality of all ambiguously influencing factors. A decision support system based on the proposed model has been developed.

The developed system will make it possible to quickly organize the work of medical personnel and thereby increase the efficiency of services provided in a medical institution by optimizing all influencing factors.

Pages: 55-60
For citation

Zhuleva S.Yu., Kroshilin A.V., Kroshilina S.V. Development of a decision support system for the organization of a medical worker's working time based on artificial intelligence methods. Biomedicine Radioengineering. 2023. V. 26. № 3. Р. 55-60. DOI: https://doi.org/ 10.18127/j15604136-202303-07 (In Russian).

References
  1. Zhuleva S.Yu., Kroshilin A.V., Kroshilina S.V. Podderzhka prinyatiya resheniy v zadachakh raspredeleniya nagruzki meditsinskikh rabotnikov na osnove metodov iskusstvenno-go intellekta. Biomeditsinskaya radioelektronika. 2018. № 8. S. 54–59.
  2. Zhuleva S.Yu., Kroshilin A.V., Kroshilina S.V. Podderzhka prinyatiya upravlenche-skikh meditsinskikh resheniy i priroda neopredelennosti v nikh. Biomeditsinskaya radio-elektronika. 2021. T. 24. № 4. S. 89–96.
  3. Rutkovskaya D., Pilinski M., Rutkovskiy L. Neyronnyye seti. geneticheskiye algo-ritmy i nechetkiye sistemy [2-e izd]. M.: Goryachaya liniya – Telekom. 2008. 452 s.
  4. Zhuleva S.Yu., Doan D.Kh., Kroshilin A.V. Raspredeleniye nagruzki meditsinskogo personala na osnove teorii nechetkikh mnozhestv. Prioritetnyye napravleniya razvitiya ob-razovaniya i nauki: Mat-ly Mezhdunar. nauch.-prakt. konf. (Cheboksary. 9 apr. 2017 g.). V 2-kh t. T. 2. Cheboksary: TsNS «Interaktiv plyus». 2017. S. 57–59.
  5. Doan D.Kh., Zhuleva S.Yu., Kroshilina S.V. Primeneniye teorii nechetkikh mnozhestv i nechetkoy logiki dlya predstavleniya meditsinskikh znaniy v sistemakh podderzhki prinyatiya resheniy meditsinskogo naznacheniya. Sovremennyy vzglyad na budushcheye nauki: Sb. statey Mezhdunar. nauch.-prakt. konf. (20 marta 2017 g., g. Kazan). V 3-kh ch. Ch. 2. Ufa: AETERNA. 2017. S. 22–25.
  6. Zhuleva S.Yu., Kroshilin A.V., Kroshilina S.V. Predstavleniye znaniy na osnove teorii nechetkikh mnozhestv v meditsinskikh predmetnykh oblastyakh. Biomeditsinskaya radio-elektronika. 2022. T. 25. № 4. S. 62–70.
Date of receipt: 25.05.2023
Approved after review: 29.05.2023
Accepted for publication: 30.05.2023