A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU).

Wang K, Hussain W, Birge JR, Schreiber MD, Adelman D

DOI: 10.1287/ijoc.2021.1062
Published: 2022 Jan-Feb
Container: INFORMS journal on computing
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1287/ijoc.2021.1062,
  title = {A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU).},
  author = {Wang K and Hussain W and Birge JR and Schreiber MD and Adelman D},
  year = {2022},
  journal = {INFORMS journal on computing},
  doi = {10.1287/ijoc.2021.1062},
  url = {https://doi.org/10.1287/ijoc.2021.1062}
}

RIS

TY  - JOUR
TI  - A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU).
AU  - Wang K
AU  - Hussain W
AU  - Birge JR
AU  - Schreiber MD
AU  - Adelman D
PY  - 2022
JO  - INFORMS journal on computing
DO  - 10.1287/ijoc.2021.1062
UR  - https://doi.org/10.1287/ijoc.2021.1062
ER  -

APA

K, W., W, H., JR, B., MD, S., & D, A. (2022). A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU).. INFORMS journal on computing. https://doi.org/10.1287/ijoc.2021.1062

Source records

pubmed · retrieved 2026-09-25T06:31:32.141Z