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Vol. 22, Art. 23 (pp. 328-343)    |    2021       

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Classification of epidemiological forecasts and application of gradient boosting in preventive medicine

Federal Government State Establishment Main Center for State Sanitary and Epidemiological Surveillance (Special Purpose) of The Russian Federation Defense Ministry
Federal State Budjet Institution Saint_Peterburg Scientific-Research Institute for physical culture

Brief summary

The article proposes a new justified classification of epidemiological forecasts of acute respiratory infections. An overview of machine learning methods is presented. Examples of the use of the gradient boosting method in the field of clinical medicine for the purpose of predicting somatic morbidity are shown. The relevance of the use of gradient boosting in predicting the incidence of infectious diseases and respiratory diseases is highlighted. The development and implementation of the forecast of acute respiratory infections in organized teams of the Armed Forces of the Russian Federation with a preliminary definition of predictors is proposed.


Key words

machine learning, gradient boosting, retrospective epidemiological analysis, orecasting, prognosis of morbidity, acute respiratory infection, organized collectives, and the Armed Forces of the Russian Federation.

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