| Autor: |
Borisova Lyudmila, Sedykh Irina, Khripunova Marina |
| Jazyk: |
English<br />French |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
E3S Web of Conferences, Vol 542, p 05007 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202454205007 |
| Popis: |
Rosstat data on the dynamics of major socially significant diseases have been studied. The relationship between such diseases has been investigated. The influence of the main socially significant diseases and the main indicators of socio-economic development of the regions of the Russian Federation on the number of abortions has been studied. The most informative signs related to socially significant diseases and socio-economic development in all countries of the world have been selected. The influence of these signs on infant mortality has been studied. Machine learning methods collected in the Data Master Azforus (DMA) program were applied. The conducted research has demonstrated the effectiveness of using machine learning methods to identify patterns linking the frequency of socially significant diseases and indicators of socio-economic development. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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