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https://elib.bsu.by/handle/123456789/291855| Title: | Forecasting cases of children disease by non-invasive forms of pneumococcal infection |
| Authors: | Sokolova, M. V. Romanova, O. N. Kolomiets, N. D. Bosiakov, S. M. |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика |
| Issue Date: | 2022 |
| Publisher: | Minsk : BSU |
| Citation: | Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the XIII Intern. Conf., Minsk, Sept. 6–10, 2022 / Belarusian State University ; eds.: Yu. Kharin [et al.]. – Minsk : BSU, 2022. – Pp. 184-186. |
| Abstract: | The forecasting of children cases (under 7 years of age) by non-invasive forms of pneumococcal infection was carried out using a mathematical model of time series. A database was used with clinical and epidemiological information about 435 patients hospitalized for 3 years. It is found out that the average number of cases is 12 children per month. The obtained results can be used for medium-term and long-term forecasting of the patient number needing medical care during a calendar year, and also for the organization and planning of a corresponding complex of preventive and therapeutic measures |
| URI: | https://elib.bsu.by/handle/123456789/291855 |
| ISBN: | 978-985-881-420-5 |
| Sponsorship: | The study was supported by State Program of Scientific Research “Convergence” (Instruction No. 1.7.1.4) |
| Licence: | info:eu-repo/semantics/restrictedAccess |
| Appears in Collections: | 2022. Computer Data Analysis and Modeling: Stochastics and Data Science |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 184-186.pdf | 254,06 kB | Adobe PDF | View/Open |
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