Indicators from DHIS2 are found to be able to forecast acute malnutrition. AUC results are presented as meanstd, [95% CI] derived from forecasting acute malnutrition across different forecast horizons using various sets of indicators and ML models. Indicators include PO (previous outcome), CF (clinical features), and S (sub-county indicator), with the “+” sign denoting the concatenation of indicators. The models assessed are WA (Window Average), LR (Logistic Regression), and GB (Gradient Boosting).
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https://figshare.com/articles/dataset/Indicators_from_DHIS2_are_found_to_be_able_to_forecast_acute_malnutrition_AUC_results_are_presented_as_meanstd_95_CI_derived_from_forecasting_acute_malnutrition_across_different_forecast_horizons_using_various_sets_of_indicators_and_ML_mode/29076806
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Indicators from DHIS2 are found to be able to forecast acute malnutrition. AUC results are presented as meanstd, [95% CI] derived from forecasting acute malnutrition across different forecast horizons using various sets of indicators and ML models. Indicators include PO (previous outcome), CF (clinical features), and S (sub-county indicator), with the “+” sign denoting the concatenation of indicators. The models assessed are WA (Window Average), LR (Logistic Regression), and GB (Gradient Boosting).
创建时间：
2025-05-14
