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Connection

Dana Edelson to ROC Curve

This is a "connection" page, showing publications Dana Edelson has written about ROC Curve.
Connection Strength

1.906
  1. Early Warning Scores With and Without Artificial Intelligence. JAMA Netw Open. 2024 Oct 01; 7(10):e2438986.
    View in: PubMed
    Score: 0.198
  2. 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: 0.159
  3. Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting: Retrospective Cohort Study. Ann Surg. 2019 06; 269(6):1059-1063.
    View in: PubMed
    Score: 0.137
  4. 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: 0.122
  5. Quick Sepsis-related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores for Detecting Clinical Deterioration in Infected Patients outside the Intensive Care Unit. Am J Respir Crit Care Med. 2017 04 01; 195(7):906-911.
    View in: PubMed
    Score: 0.118
  6. Real-Time Risk Prediction on the Wards: A Feasibility Study. Crit Care Med. 2016 08; 44(8):1468-73.
    View in: PubMed
    Score: 0.112
  7. The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016 May; 102:1-5.
    View in: PubMed
    Score: 0.109
  8. 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: 0.108
  9. Differences in vital signs between elderly and nonelderly patients prior to ward cardiac arrest. Crit Care Med. 2015 Apr; 43(4):816-22.
    View in: PubMed
    Score: 0.102
  10. Predicting clinical deterioration in the hospital: the impact of outcome selection. Resuscitation. 2013 May; 84(5):564-8.
    View in: PubMed
    Score: 0.086
  11. Derivation of a cardiac arrest prediction model using ward vital signs*. Crit Care Med. 2012 Jul; 40(7):2102-8.
    View in: PubMed
    Score: 0.085
  12. Predicting cardiac arrest on the wards: a nested case-control study. Chest. 2012 May; 141(5):1170-1176.
    View in: PubMed
    Score: 0.081
  13. Development and Validation of a Machine Learning Model for Early Detection of Untreated Infection. Crit Care Explor. 2024 Oct 01; 6(10):e1165.
    View in: PubMed
    Score: 0.049
  14. 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: 0.049
  15. Development and external validation of deep learning clinical prediction models using variable-length time series data. J Am Med Inform Assoc. 2024 May 20; 31(6):1322-1330.
    View in: PubMed
    Score: 0.048
  16. Identifying infected patients using semi-supervised and transfer learning. J Am Med Inform Assoc. 2022 09 12; 29(10):1696-1704.
    View in: PubMed
    Score: 0.043
  17. 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: 0.042
  18. Comparison of Machine Learning Methods for Predicting Outcomes After In-Hospital Cardiac Arrest. Crit Care Med. 2022 02 01; 50(2):e162-e172.
    View in: PubMed
    Score: 0.041
  19. Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury. JAMA Netw Open. 2020 08 03; 3(8):e2012892.
    View in: PubMed
    Score: 0.037
  20. 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: 0.037
  21. Predictors of In-Hospital Mortality After Rapid Response Team Calls in a 274 Hospital Nationwide Sample. Crit Care Med. 2018 07; 46(7):1041-1048.
    View in: PubMed
    Score: 0.032
  22. The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model. Crit Care Med. 2018 07; 46(7):1070-1077.
    View in: PubMed
    Score: 0.032
  23. 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: 0.032
  24. Development of a Multicenter Ward-Based AKI Prediction Model. Clin J Am Soc Nephrol. 2016 11 07; 11(11):1935-1943.
    View in: PubMed
    Score: 0.028
  25. Neurologic prognostication and bispectral index monitoring after resuscitation from cardiac arrest. Resuscitation. 2010 Sep; 81(9):1133-7.
    View in: PubMed
    Score: 0.018
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.