Development of a decision support system for the organization of a medical worker's working time based on artificial intelligence methods
- 1,2,3 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.
- Received
- 25.05.2023
- Approved after review
- 29.05.2023
- Accepted
- 30.05.2023
How to cite
Жулева С.Ю., Крошилин А.В., Крошилина С.В. Разработка системы поддержки принятия решений для организации рабочего времени медицинского работника на основе методов искусственного интеллекта // Биомедицинская радиоэлектроника. 2023. T. 26. № 3. С. 55-60. DOI: https://doi.org/10.18127/j15604136-202303-07
References
- 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.
- 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.
- Rutkovskaya D., Pilinski M., Rutkovskiy L. Neyronnyye seti. geneticheskiye algo-ritmy i nechetkiye sistemy [2-e izd]. M.: Goryachaya liniya – Telekom. 2008. 452 s.
- 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.
- 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.
- 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.