يعرض 1 - 19 نتائج من 19 نتيجة بحث عن '"6 %- 81"', وقت الاستعلام: 0.37s تنقيح النتائج
  1. 1
    Academic Journal
    Accuracy of transitions from routine to ICU care at fixed sensitivity thresholds and ICU to routine care at fixed specificity thresholds.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Accuracy_of_transitions_from_routine_to_ICU_care_at_fixed_sensitivity_thresholds_and_ICU_to_routine_care_at_fixed_specificity_thresholds_/25105092

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s004
    https://figshare.com/articles/journal_contribution/Accuracy_of_transitions_from_routine_to_ICU_care_at_fixed_sensitivity_thresholds_and_ICU_to_routine_care_at_fixed_specificity_thresholds_/25105092

    View record in BASE

    أضف إلى المفضلة
  2. 2
    Academic Journal
    Medication data for Institutional Criticality Index-dynamic models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Medication_data_for_Institutional_Criticality_Index-dynamic_models_/25105086

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s002
    https://figshare.com/articles/journal_contribution/Medication_data_for_Institutional_Criticality_Index-dynamic_models_/25105086

    View record in BASE

    أضف إلى المفضلة
  3. 3
    Academic Journal
    Independent variables for Institutional Criticality Index-dynamic models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Independent_variables_for_Institutional_Criticality_Index-dynamic_models_/25105083

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s001
    https://figshare.com/articles/journal_contribution/Independent_variables_for_Institutional_Criticality_Index-dynamic_models_/25105083

    View record in BASE

    أضف إلى المفضلة
  4. 4
    Academic Journal
    Accuracy of transitions from routine to ICU care at fixed sensitivity thresholds and ICU to routine care at fixed specificity thresholds.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Accuracy_of_transitions_from_routine_to_ICU_care_at_fixed_sensitivity_thresholds_and_ICU_to_routine_care_at_fixed_specificity_thresholds_/25105092

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s004

    View record in BASE

    أضف إلى المفضلة
  5. 5
    Academic Journal
    Independent variables for Institutional Criticality Index-dynamic models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Independent_variables_for_Institutional_Criticality_Index-dynamic_models_/25105083

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s001

    View record in BASE

    أضف إلى المفضلة
  6. 6
    Academic Journal
    Medication data for Institutional Criticality Index-dynamic models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Medication_data_for_Institutional_Criticality_Index-dynamic_models_/25105086

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s002

    View record in BASE

    أضف إلى المفضلة
  7. 7
    Academic Journal
    Details of imputation for Institutional Criticality Index-dynamic models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/journal_contribution/Details_of_imputation_for_Institutional_Criticality_Index-dynamic_models_/25105089

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.s003
    https://figshare.com/articles/journal_contribution/Details_of_imputation_for_Institutional_Criticality_Index-dynamic_models_/25105089

    View record in BASE

    أضف إلى المفضلة
  8. 8
    Image
    Fig 1 -

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Fig_1_-/25105095

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g001
    https://figshare.com/articles/figure/Fig_1_-/25105095

    View record in BASE

    أضف إلى المفضلة
  9. 9
    Performance metrics of the Dynamic Criticality Index models developed from the multi-institutional database applied to the single-site test dataset (A) and the single-site Dynamic Criticality Index models applied to the single-site test dataset (B).

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Performance_metrics_of_the_Dynamic_Criticality_Index_models_developed_from_the_multi-institutional_database_applied_to_the_single-site_test_dataset_A_and_the_single-site_Dynamic_Criticality_Index_models_applied_to_the_single-site_test_datas/25105110

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t002
    https://figshare.com/articles/dataset/Performance_metrics_of_the_Dynamic_Criticality_Index_models_developed_from_the_multi-institutional_database_applied_to_the_single-site_test_dataset_A_and_the_single-site_Dynamic_Criticality_Index_models_applied_to_the_single-site_test_datas/25105110

    View record in BASE

    أضف إلى المفضلة
  10. 10
    Single-site Dynamic Criticality Index performance metrics for sensitivities of 0.85, 0.90, 0.95, and 0.99 representing four potential decision thresholds for the four future time periods.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Single-site_Dynamic_Criticality_Index_performance_metrics_for_sensitivities_of_0_85_0_90_0_95_and_0_99_representing_four_potential_decision_thresholds_for_the_four_future_time_periods_/25105113

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t003
    https://figshare.com/articles/dataset/Single-site_Dynamic_Criticality_Index_performance_metrics_for_sensitivities_of_0_85_0_90_0_95_and_0_99_representing_four_potential_decision_thresholds_for_the_four_future_time_periods_/25105113

    View record in BASE

    أضف إلى المفضلة
  11. 11
    Image
    Variable importance for the single-site and multi-institutional Dynamic Criticality Index models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Variable_importance_for_the_single-site_and_multi-institutional_Dynamic_Criticality_Index_models_/25105101

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g003
    https://figshare.com/articles/figure/Variable_importance_for_the_single-site_and_multi-institutional_Dynamic_Criticality_Index_models_/25105101

    View record in BASE

    أضف إلى المفضلة
  12. 12
    Image
    Fig 4 -

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Fig_4_-/25105104

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g004
    https://figshare.com/articles/figure/Fig_4_-/25105104

    View record in BASE

    أضف إلى المفضلة
  13. 13
    Population characteristics of children’s national patient sample.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Population_characteristics_of_children_s_national_patient_sample_/25105107

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t001
    https://figshare.com/articles/dataset/Population_characteristics_of_children_s_national_patient_sample_/25105107

    View record in BASE

    أضف إلى المفضلة
  14. 14
    Image
    Variable importance for the single-site and multi-institutional Dynamic Criticality Index models.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Variable_importance_for_the_single-site_and_multi-institutional_Dynamic_Criticality_Index_models_/25105101

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g003

    View record in BASE

    أضف إلى المفضلة
  15. 15
    Image
    Fig 1 -

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Fig_1_-/25105095

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g001

    View record in BASE

    أضف إلى المفضلة
  16. 16
    Population characteristics of children’s national patient sample.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Population_characteristics_of_children_s_national_patient_sample_/25105107

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t001

    View record in BASE

    أضف إلى المفضلة
  17. 17
    Performance metrics of the Dynamic Criticality Index models developed from the multi-institutional database applied to the single-site test dataset (A) and the single-site Dynamic Criticality Index models applied to the single-site test dataset (B).

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Performance_metrics_of_the_Dynamic_Criticality_Index_models_developed_from_the_multi-institutional_database_applied_to_the_single-site_test_dataset_A_and_the_single-site_Dynamic_Criticality_Index_models_applied_to_the_single-site_test_datas/25105110

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t002

    View record in BASE

    أضف إلى المفضلة
  18. 18
    Single-site Dynamic Criticality Index performance metrics for sensitivities of 0.85, 0.90, 0.95, and 0.99 representing four potential decision thresholds for the four future time periods.

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/dataset/Single-site_Dynamic_Criticality_Index_performance_metrics_for_sensitivities_of_0_85_0_90_0_95_and_0_99_representing_four_potential_decision_thresholds_for_the_four_future_time_periods_/25105113

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.t003

    View record in BASE

    أضف إلى المفضلة
  19. 19
    Image
    Fig 4 -

    المؤلفون: Anita K. Patel, Eduardo Trujillo-Rivera, James M. Chamberlain, Hiroki Morizono, Murray M. Pollack

    مصطلحات موضوعية: Medicine, Molecular Biology, Biotechnology, Cancer, Science Policy, Infectious Diseases, Biological Sciences not elsewhere classified, predict future need, pediatric inpatients admitted, machine learning model, dynamic criticality index, age 68 months, 906 &# 8211, 754 &# 8211, 6 &# 8211, 6 %- 81, 493 &# 8211, 262 &# 8211, 2 %- 76, 157 ), 15 &# 8211, predicting care locations, predict future care, 24 &# 8211, 18 &# 8211, 12 &# 8211, th , st , site test dataset

    Time: 47

    Relation: https://figshare.com/articles/figure/Fig_4_-/25105104

    الاتاحة: https://doi.org/10.1371/journal.pone.0288233.g004

    View record in BASE

    أضف إلى المفضلة
أدوات البحث: أحصل على تغذية RSS – أرسل هذا البحث بالبريد الإلكتروني – حفظ البحث – جدول التنبيهات: لا شيء