Shapley values from a Gaussian process regression rank income, workforce, HIV testing, unemployment, and population as the most influential socio-economic predictors of tuberculosis infection rates, but the regression only matches 10 of 87 Russian regions within 10 percent error.
Effects of social protection on tuberculosis treatment outcomes in low or middle-income and in high-burden countries: systematic review and meta-analysis
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Feature importance of socio-economic parameters in Tuberculosis modeling
Shapley values from a Gaussian process regression rank income, workforce, HIV testing, unemployment, and population as the most influential socio-economic predictors of tuberculosis infection rates, but the regression only matches 10 of 87 Russian regions within 10 percent error.