ПРОГНОЗИРОВАНИЕ РАСПРОСТРАНЕНИЯ БОЛЕЗНЕЙ В ТРОПИЧЕСКИХ ЗО-НАХ С ПОМОЩЬЮ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ

Translated title of the contribution: Forecasting the distribution of diseases in tropical zones using machine learning methods

Alexey A. Kolesnikov, Pavel M. Kikin

Research output: Contribution to journalConference articlepeer-review

Abstract

Infection with tropical parasitic diseases, according to WHO, has a huge impact on the health of more than 40 million people worldwide and is the second leading cause of immunodeficiency. The number of infections is influenced by many factors - climatic, demographic, vegetation cover and a number of others. The article presents a study and an assessment of the degree of influence of each of these factors, as well as a comparison of the quality of forecasting by separate methods of geo-informational analysis and machine learning and the possibility of their ensemble.

Translated title of the contributionForecasting the distribution of diseases in tropical zones using machine learning methods
Original languageRussian
Pages (from-to)371-376
Number of pages6
JournalCEUR Workshop Proceedings
Volume2534
StatePublished - 12 Jan 2020
Event2019 All-Russian Conference "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2019 - Berdsk, Russian Federation
Duration: 26 Aug 201930 Aug 2019

Scopus subject areas

  • Computer Science(all)

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