Machine Learning Methods for Predicting Patient-Level Emergency Department Workload
Article Properties
-
LanguageEnglish
-
DOI (url)
-
Publication Date2023/01/01
-
Indian UGC (journal)
-
Refrences30
-
Citations3
-
Joshua W. Joseph ORCID (unauthenticated)
-
Evan L. Leventhal
-
Anne V. Grossestreuer
-
Paul C. Chen
-
Benjamin A. White
-
Larry A. Nathanson
-
Noémie Elhadad
-
Leon D. Sanchez
Cite
Joseph, Joshua W., et al. “Machine Learning Methods for Predicting Patient-Level Emergency Department Workload”. The Journal of Emergency Medicine, vol. 64, no. 1, 2023, pp. 83-92, https://doi.org/10.1016/j.jemermed.2022.10.002.
Joseph, J. W., Leventhal, E. L., Grossestreuer, A. V., Chen, P. C., White, B. A., Nathanson, L. A., Elhadad, N., & Sanchez, L. D. (2023). Machine Learning Methods for Predicting Patient-Level Emergency Department Workload. The Journal of Emergency Medicine, 64(1), 83-92. https://doi.org/10.1016/j.jemermed.2022.10.002
Joseph, Joshua W., Evan L. Leventhal, Anne V. Grossestreuer, Paul C. Chen, Benjamin A. White, Larry A. Nathanson, Noémie Elhadad, and Leon D. Sanchez. “Machine Learning Methods for Predicting Patient-Level Emergency Department Workload”. The Journal of Emergency Medicine 64, no. 1 (2023): 83-92. https://doi.org/10.1016/j.jemermed.2022.10.002.
Joseph JW, Leventhal EL, Grossestreuer AV, Chen PC, White BA, Nathanson LA, et al. Machine Learning Methods for Predicting Patient-Level Emergency Department Workload. The Journal of Emergency Medicine. 2023;64(1):83-92.
Journal Categories
Medicine
Internal medicine
Medical emergencies
Critical care
Intensive care
First aid
Medicine
Internal medicine
Special situations and conditions
Medicine
Medicine (General)
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Should age be incorporated into the adult triage algorithm in the emergency department? | The American Journal of Emergency Medicine |
| 10 | 2021 |
| Gender disparities in cardiac catheterization rates among emergency department patients with chest pain | 2021 | |||
| Patient Assignment Models in the Emergency Department | Emergency Medicine Clinics of North America |
| 5 | 2020 |
Deep learning in clinical natural language processing: a methodical review | Journal of the American Medical Informatics Association |
| 186 | 2020 |
Deep‐learning approaches to identify critically Ill patients at emergency department triage using limited information | Journal of the American College of Emergency Physicians Open |
| 17 | 2020 |
Refrences Analysis
The category
Medicine: Medicine (General) 20
is the most frequently represented among the references in this article. It primarily includes studies from Annals of Emergency Medicine and Emergency Medicine Clinics of North America. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
An ensemble model for predicting dispositions of emergency department patients | BMC Medical Informatics and Decision Making |
| 2024 | |
Race and Ethnicity and Primary Language in Emergency Department Triage | JAMA Network Open |
| 1 | 2023 |
| Enhanced neural network-based attack investigation framework for network forensics: Identification, detection, and analysis of the attack | Computers & Security |
| 2023 |
Citations Analysis
The category
Medicine: Medicine (General) 2
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Race and Ethnicity and Primary Language in Emergency Department Triage and was published in 2023. The most recent citation comes from a 2024 study titled An ensemble model for predicting dispositions of emergency department patients. This article reached its peak citation in 2023, with 2 citations. It has been cited in 3 different journals, 66% of which are open access. Among related journals, the BMC Medical Informatics and Decision Making cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.