Вивчення зв’язку між туберкульозом та соціально-економічними, медичними, демографічними чинниками в Україні

Ukraine is currently experiencing a new, ongoing tuberculosis offensive. Our study analyzes the impact of various socioeconomic and medical factors, including the number of specialized hospitals, fluoroscopic examinations of the population, the number of healthcare workers, the level of alcohol and drug abuse, and others, on the prevalence of tuberculosis among different demographic groups in Ukraine. Artificial intelligence methods made it possible to identify key factors contributing to the growth or decline in tuberculosis incidence. The results of the SHAP (SHapley Additive exPlanations) analysis, which offers a methodology for interpreting complex machine learning models, shows the most important factors that influence the incidence of tuberculosis in Ukraine. The sensitivity analysis provided more important and detailed information, which confirmed the results of the SHAP analysis.

Publication Details

Journal
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Published
2025-03-28
Primary Topic
Methane Hydrates and Related Phenomena
Type
article
Field-Weighted Citation Impact
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article

Вивчення зв’язку між туберкульозом та соціально-економічними, медичними, демографічними чинниками в Україні

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Methane Hydrates and Related Phenomena
article

Вивчення зв’язку між туберкульозом та соціально-економічними, медичними, демографічними чинниками в Україні

article en

Abstract

Ukraine is currently experiencing a new, ongoing tuberculosis offensive. Our study analyzes the impact of various socioeconomic and medical factors, including the number of specialized hospitals, fluoroscopic examinations of the population, the number of healthcare workers, the level of alcohol and drug abuse, and others, on the prevalence of tuberculosis among different demographic groups in Ukraine. Artificial intelligence methods made it possible to identify key factors contributing to the growth or decline in tuberculosis incidence. The results of the SHAP (SHapley Additive exPlanations) analysis, which offers a methodology for interpreting complex machine learning models, shows the most important factors that influence the incidence of tuberculosis in Ukraine. The sensitivity analysis provided more important and detailed information, which confirmed the results of the SHAP analysis.

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Good health and well-being
Openalex Percentile: Top 51%
Methane Hydrates and Related Phenomena
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