المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

المصدر: PLoS ONE, Vol 19, Iss 1, p e0296064 (2024)

مصطلحات موضوعية: Medicine, Science

وصف الملف: electronic resource

Relation: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0296064&type=printable; https://doaj.org/toc/1932-6203

URL الوصول: https://doaj.org/article/31dcb584647f49fcbd1397f89f934efb

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/journal_contribution/NNA_parameters_evaluated_to_BMMR_forecast_/25120602

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.s007
https://figshare.com/articles/journal_contribution/NNA_parameters_evaluated_to_BMMR_forecast_/25120602

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/dataset/Computer_code_used_for_the_analyses_/25120587

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.s002
https://figshare.com/articles/dataset/Computer_code_used_for_the_analyses_/25120587

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/dataset/Historical_data_of_BMMR_from_1996_2022_/25120584

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.s001
https://figshare.com/articles/dataset/Historical_data_of_BMMR_from_1996_2022_/25120584

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/Diagnostic_plots_for_ARIMA_0_1_3_2_0_0_4_on_Brazilian_Maternal_Mortality_Ratios_1996_2019_A_residual_plot_B_partial_autocorrelation_function_plot_of_residual_and_C_histogram_of_residual_/25120596

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.s005
https://figshare.com/articles/figure/Diagnostic_plots_for_ARIMA_0_1_3_2_0_0_4_on_Brazilian_Maternal_Mortality_Ratios_1996_2019_A_residual_plot_B_partial_autocorrelation_function_plot_of_residual_and_C_histogram_of_residual_/25120596

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/S4_Fig_-/25120599

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.s006
https://figshare.com/articles/figure/S4_Fig_-/25120599

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_ARIMA_0_1_3_2_0_0_4_/25120611

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.g003
https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_ARIMA_0_1_3_2_0_0_4_/25120611

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/Brazilian_Maternal_Mortality_Ratio_1996_2021_highlighting_the_H_sub_1_sub_N_sub_1_sub_-influenza_Flu_pandemic_2009_and_the_COVID-19_pandemic_2020_2021_/25120605

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.g001
https://figshare.com/articles/figure/Brazilian_Maternal_Mortality_Ratio_1996_2021_highlighting_the_H_sub_1_sub_N_sub_1_sub_-influenza_Flu_pandemic_2009_and_the_COVID-19_pandemic_2020_2021_/25120605

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_the_NNA_8_6_1_6_model_/25120614

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.g004
https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_the_NNA_8_6_1_6_model_/25120614

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_the_Holt-Winters_multiplicative_method_/25120608

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.g002
https://figshare.com/articles/figure/Forecast_of_the_quarterly_Brazil_Maternal_Mortality_Ratio_up_to_2025_using_the_Holt-Winters_multiplicative_method_/25120608

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/dataset/Performance_parameters_of_evaluated_models_/25120617

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.t001
https://figshare.com/articles/dataset/Performance_parameters_of_evaluated_models_/25120617

المؤلفون: Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

مصطلحات موضوعية: Medicine, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, public health agencies, prediction results beyond, neural networks autoregression, distressing fatality rate, current mortality rate, 99 &# 177, 1996 &# 8211, 000 live births, highest mortality peak, country &# 8217, although nna provided, winters exponential smoothing, historical bmmr series, 19 pandemic scenario, nna ), highest number, country experienced, 19 pandemic, %22">xlink ">, temporal correlation, study revealed, study investigates, second quarter, sample data, previous period, mean bmmr

Relation: https://figshare.com/articles/dataset/Quarterly_forecast_of_the_Brazilian_Maternal_Mortality_Ratio_out_of_1_000_live_births_up_to_2025_in_a_controlled_COVID-19_scenario_comparing_forecasted_values_with_reported_values_2020_2021_/25120620

الاتاحة: https://doi.org/10.1371/journal.pone.0296064.t002
https://figshare.com/articles/dataset/Quarterly_forecast_of_the_Brazilian_Maternal_Mortality_Ratio_out_of_1_000_live_births_up_to_2025_in_a_controlled_COVID-19_scenario_comparing_forecasted_values_with_reported_values_2020_2021_/25120620