يعرض 1 - 20 نتائج من 32 نتيجة بحث عن '"Eduardo Trujillo-Rivera"', وقت الاستعلام: 0.44s تنقيح النتائج
  1. 1
    Academic Journal
    External evaluation of the Dynamic Criticality Index: A machine learning model to predict future need for ICU care in hospitalized pediatric patients.

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

    المصدر: PLoS ONE, Vol 19, Iss 1, p e0288233 (2024)

    مصطلحات موضوعية: Medicine, Science

    وصف الملف: electronic resource

    Relation: https://doaj.org/toc/1932-6203

    URL الوصول: https://doaj.org/article/692a1eb56f1944689e9197b75ba23ef9

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  2. 2
    Academic Journal
    The criticality Index-mortality: A dynamic machine learning prediction algorithm for mortality prediction in children cared for in an ICU

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

    المصدر: Frontiers in Pediatrics, Vol 10 (2022)

    مصطلحات موضوعية: prediction algorithm, dynamic outcome prediction, mortality prediction, criticality index, machine learning, Pediatrics, RJ1-570

    وصف الملف: electronic resource

    Relation: https://www.frontiersin.org/articles/10.3389/fped.2022.1023539/full; https://doaj.org/toc/2296-2360

    URL الوصول: https://doaj.org/article/f0657d4321e64261b52e8a4aae1ded7e

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  3. 3
    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

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  4. 4
    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

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

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  6. 6
    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

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  7. 7
    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

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  8. 8
    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

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  9. 9
    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

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  10. 10
    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

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  11. 11
    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

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  12. 12
    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

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  13. 13
    National Intravenous Acetaminophen Use in Pediatric Inpatients From 2011–2016

    المؤلفون: Anita K, Patel, Jiaxiang, Gai, Eduardo, Trujillo-Rivera, Farhana, Faruqe, Dongkyu, Kim, James E, Bost, Murray M, Pollack

    المصدر: J Pediatr Pharmacol Ther

    مصطلحات موضوعية: stomatognathic diseases, Research, digestive, oral, and skin physiology, Pediatrics, Perinatology and Child Health, Pharmacology (medical)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99e33e4973f773ef92c427bcb6e77175
    https://doi.org/10.5863/1551-6776-27.4.358

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  14. 14
    Clinical Instability Is a Sign of Severity of Illness: A Cohort Study

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

    المصدر: Pediatric Critical Care Medicine.

    مصطلحات موضوعية: Pediatrics, Perinatology and Child Health, Critical Care and Intensive Care Medicine

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::1383567ff9880a37755a020630cbe1a7
    https://doi.org/10.1097/pcc.0000000000003255

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  15. 15
    Sedation, Analgesia, and Neuromuscular Blockade: An Assessment of Practices From 2009 to 2016 in a National Sample of 66,443 Pediatric Patients Cared for in the ICU*

    المؤلفون: James M. Chamberlain, Eduardo Trujillo-Rivera, Dongkyu Kim, T. Elizabeth Workman, James E. Bost, Murray M. Pollack, Hiroki Morizono, Farhana Faruqe, Qing Zeng-Treitler, Anita K. Patel, Julia A Heneghan

    المصدر: Pediatric Critical Care Medicine. 21:e599-e609

    مصطلحات موضوعية: medicine.drug_class, Sedation, Analgesic, Critical Care and Intensive Care Medicine, 03 medical and health sciences, 0302 clinical medicine, Interquartile range, 030225 pediatrics, medicine, Humans, Hypnotics and Sedatives, Child, Retrospective Studies, Analgesics, Neuromuscular Blockade, business.industry, Infant, 030208 emergency & critical care medicine, Medication administration, Intensive Care Units, Opioid, Anesthesia, Sedative, Pediatrics, Perinatology and Child Health, National database, Analgesia, medicine.symptom, business, medicine.drug

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::799ec421a3ebe1ae19c05f9a65248f2a
    https://doi.org/10.1097/pcc.0000000000002351

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  16. 16
    Association of Intravenous Acetaminophen Administration With the Duration of Intravenous Opioid Use Among Hospitalized Pediatric Patients

    المؤلفون: Anita K. Patel, Jiaxiang Gai, Eduardo Trujillo-Rivera, Farhana Faruqe, Dongkyu Kim, James E. Bost, Murray M. Pollack

    المصدر: JAMA Network Open

    مصطلحات موضوعية: Adult, Male, Inpatients, Pain, Postoperative, Adolescent, Research, Infant, Newborn, Infant, General Medicine, Analgesics, Non-Narcotic, Opioid-Related Disorders, Pediatrics, United States, Analgesics, Opioid, Young Adult, Online Only, Child, Preschool, Humans, Administration, Intravenous, Female, Child, Acetaminophen, Original Investigation

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b23d61547cbc205ed99c35161c061872
    https://pubmed.ncbi.nlm.nih.gov/34932106

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  17. 17
    Datasheet1_The criticality Index-mortality: A dynamic machine learning prediction algorithm for mortality prediction in children cared for in an ICU.docx

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

    مصطلحات موضوعية: Foetal Development and Medicine, Obstetrics and Gynaecology, Paediatrics, Paediatrics and Reproductive Medicine not elsewhere classified, prediction algorithm, dynamic outcome prediction, mortality prediction, criticality index, machine learning

    Relation: https://figshare.com/articles/dataset/Datasheet1_The_criticality_Index-mortality_A_dynamic_machine_learning_prediction_algorithm_for_mortality_prediction_in_children_cared_for_in_an_ICU_docx/21654539

    الاتاحة: https://doi.org/10.3389/fped.2022.1023539.s001
    https://figshare.com/articles/dataset/Datasheet1_The_criticality_Index-mortality_A_dynamic_machine_learning_prediction_algorithm_for_mortality_prediction_in_children_cared_for_in_an_ICU_docx/21654539

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  18. 18
    The Burning of Sugarcane Plantation in the Tropics Modifies the Microbial and Enzymatic Processes in Soil and Rhizosphere

    المؤلفون: M. C. Rivera-Cruz, Antonio Trujillo-Narcía, Eduardo Trujillo-Rivera, M. Magaña-Aquino

    المصدر: Journal of Soil Science and Plant Nutrition. 19:906-919

    مصطلحات موضوعية: 0106 biological sciences, Rhizosphere, Soil test, Phosphorus, Soil organic matter, Soil Science, Biomass, chemistry.chemical_element, 04 agricultural and veterinary sciences, Plant Science, Soil carbon, Phosphate solubilizing bacteria, 01 natural sciences, Agronomy, chemistry, Loam, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Agronomy and Crop Science, 010606 plant biology & botany

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::99f9a89b0b6d4ce2b17078ecb6418d07
    https://doi.org/10.1007/s42729-019-00089-w

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  19. 19
    1011: THE ASSOCIATION OF IV ACETAMINOPHEN WITH THE DURATION OF IV OPIOID USE IN PEDIATRIC INPATIENTS

    المؤلفون: Anita Patel, Jiaxiang Gai, Eduardo Trujillo-Rivera, Farhana Faruqe, Dongkyu Kim, James Bost, Murray Pollack

    المصدر: Critical Care Medicine. 50:502-502

    مصطلحات موضوعية: Critical Care and Intensive Care Medicine

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::f5400e9f6fb187bdea29c4739dcd244a
    https://doi.org/10.1097/01.ccm.0000810368.06854.74

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  20. 20
    A Novel Deep Learning Pipeline to Analyze Temporal Clinical Data

    المؤلفون: James E. Bost, Julia A Heneghan, Murray M. Pollack, Qing Zeng-Treitler, T. Elizabeth Workman, Michael Hirezi, Anita K. Patel, Eduardo Trujillo-Rivera

    المصدر: IEEE BigData

    مصطلحات موضوعية: business.industry, Computer science, Deep learning, Pipeline (computing), 020208 electrical & electronic engineering, 020207 software engineering, 02 engineering and technology, Missing data, Machine learning, computer.software_genre, Convolutional neural network, Intensive care unit, Temporal database, Task (project management), law.invention, Data visualization, Binary classification, law, 0202 electrical engineering, electronic engineering, information engineering, Artificial intelligence, business, computer

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::c15a940c33a83007a9ed303bb21fb13d
    https://doi.org/10.1109/bigdata.2018.8622099

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