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| Martinez DA, Levin SR, Klein EY, et al. (2020) Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data. Annals of Emergency Medicine |
| Ehmann MR, Klein EY, Hinson JS. (2020) Evidence-based Consensus on Intravenous Contrast Media and Acute Kidney Injury Will Improve Patient Care in the Emergency Department. Radiology. 200247 |
| Hinson JS, Ehmann MR, Al Jalbout N, et al. (2020) Risk of Acute Kidney Injury Associated With Medication Administration in the Emergency Department. The Journal of Emergency Medicine |
| Hinson JS, Al Jalbout N, Ehmann MR, et al. (2019) Acute kidney injury following contrast media administration in the septic patient: A retrospective propensity-matched analysis. Journal of Critical Care. 51: 111-116 |
| Hinson JS, Martinez DA, Schmitz PSK, et al. (2018) Accuracy of emergency department triage using the Emergency Severity Index and independent predictors of under-triage and over-triage in Brazil: a retrospective cohort analysis. International Journal of Emergency Medicine. 11: 3 |
| Hinson JS, Martinez DA, Grams MS, et al. (2018) 1EMF Prediction of Acute Kidney Injury in the Emergency Department Using Electronic Health Record Data and Machine Learning Methods Annals of Emergency Medicine. 72 |
| Levin S, Toerper M, Hamrock E, et al. (2017) Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index. Annals of Emergency Medicine |
| Hinson JS, Ehmann MR, Fine DM, et al. (2017) Risk of Acute Kidney Injury After Intravenous Contrast Media Administration. Annals of Emergency Medicine |