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Connection

Dana Edelson to Intensive Care Units

This is a "connection" page, showing publications Dana Edelson has written about Intensive Care Units.
Connection Strength

5.146
  1. Investigating the Impact of Different Suspicion of Infection Criteria on the Accuracy of Quick Sepsis-Related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores. Crit Care Med. 2017 Nov; 45(11):1805-1812.
    View in: PubMed
    Score: 0.435
  2. Real-Time Risk Prediction on the Wards: A Feasibility Study. Crit Care Med. 2016 08; 44(8):1468-73.
    View in: PubMed
    Score: 0.399
  3. Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation. J Hosp Med. 2016 11; 11(11):757-762.
    View in: PubMed
    Score: 0.396
  4. The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016 May; 102:1-5.
    View in: PubMed
    Score: 0.386
  5. Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards. Crit Care Med. 2016 Feb; 44(2):368-74.
    View in: PubMed
    Score: 0.385
  6. Multicenter development and validation of a risk stratification tool for ward patients. Am J Respir Crit Care Med. 2014 Sep 15; 190(6):649-55.
    View in: PubMed
    Score: 0.350
  7. Relationship between ICU bed availability, ICU readmission, and cardiac arrest in the general wards. Crit Care Med. 2014 Sep; 42(9):2037-41.
    View in: PubMed
    Score: 0.349
  8. Predicting clinical deterioration in the hospital: the impact of outcome selection. Resuscitation. 2013 May; 84(5):564-8.
    View in: PubMed
    Score: 0.305
  9. Sifting through the heterogeneity of the Rapid Response System literature. Resuscitation. 2012 Dec; 83(12):1419-20.
    View in: PubMed
    Score: 0.305
  10. Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score. Crit Care Explor. 2025 Apr 01; 7(4):e1232.
    View in: PubMed
    Score: 0.182
  11. Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score. Crit Care Explor. 2025 Apr; 7(4):e1232.
    View in: PubMed
    Score: 0.182
  12. Early Warning Scores With and Without Artificial Intelligence. JAMA Netw Open. 2024 Oct 01; 7(10):e2438986.
    View in: PubMed
    Score: 0.176
  13. Less is more: Detecting clinical deterioration in the hospital with machine learning using only age, heart rate, and respiratory rate. Resuscitation. 2021 11; 168:6-10.
    View in: PubMed
    Score: 0.142
  14. Accuracy of Clinicians' Ability to Predict the Need for Intensive Care Unit Readmission. Ann Am Thorac Soc. 2020 07; 17(7):847-853.
    View in: PubMed
    Score: 0.131
  15. Comparison of Early Warning Scoring Systems for Hospitalized Patients With and Without Infection at Risk for In-Hospital Mortality and Transfer to the Intensive Care Unit. JAMA Netw Open. 2020 05 01; 3(5):e205191.
    View in: PubMed
    Score: 0.129
  16. Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data. Ann Am Thorac Soc. 2018 07; 15(7):846-853.
    View in: PubMed
    Score: 0.114
  17. Accuracy Comparisons between Manual and Automated Respiratory Rate for Detecting Clinical Deterioration in Ward Patients. J Hosp Med. 2018 07 01; 13(7):486-487.
    View in: PubMed
    Score: 0.111
  18. Location of In-Hospital Cardiac Arrest in the United States-Variability in Event Rate and Outcomes. J Am Heart Assoc. 2016 09 29; 5(10).
    View in: PubMed
    Score: 0.101
  19. The value of clinical judgment in the detection of clinical deterioration. JAMA Intern Med. 2015 Mar; 175(3):456-8.
    View in: PubMed
    Score: 0.090
  20. A prospective study of nighttime vital sign monitoring frequency and risk of clinical deterioration. JAMA Intern Med. 2013 Sep 09; 173(16):1554-5.
    View in: PubMed
    Score: 0.082
  21. Derivation of a cardiac arrest prediction model using ward vital signs*. Crit Care Med. 2012 Jul; 40(7):2102-8.
    View in: PubMed
    Score: 0.075
  22. Patient acuity rating: quantifying clinical judgment regarding inpatient stability. J Hosp Med. 2011 Oct; 6(8):475-9.
    View in: PubMed
    Score: 0.071
  23. Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score. Crit Care Explor. 2024 Jul 01; 6(7):e1116.
    View in: PubMed
    Score: 0.043
  24. Executive Summary: Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU. Crit Care Med. 2024 02 01; 52(2):307-313.
    View in: PubMed
    Score: 0.042
  25. Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023. Crit Care Med. 2024 02 01; 52(2):314-330.
    View in: PubMed
    Score: 0.042
  26. The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial. Crit Care Med. 2022 09 01; 50(9):1339-1347.
    View in: PubMed
    Score: 0.038
  27. Comparison of early warning scores for predicting clinical deterioration and infection in obstetric patients. BMC Pregnancy Childbirth. 2022 Apr 06; 22(1):295.
    View in: PubMed
    Score: 0.037
  28. Association Between Survival and Time of Day for Rapid Response Team Calls in a National Registry. Crit Care Med. 2017 10; 45(10):1677-1682.
    View in: PubMed
    Score: 0.027
  29. Obstructive sleep apnea and adverse outcomes in surgical and nonsurgical patients on the wards. J Hosp Med. 2015 Sep; 10(9):592-8.
    View in: PubMed
    Score: 0.023
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.