Concurrent Prediction of Length of Stay, Mortality, and Total Charges in Patients with Acute Lymphoblastic Leukemia Using Continuous Machine Learning
- DOI
- 10.3390/informatics13040047
- Published
- 2026-03-24
- Container
- Informatics
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/informatics13040047,
title = {Concurrent Prediction of Length of Stay, Mortality, and Total Charges in Patients with Acute Lymphoblastic Leukemia Using Continuous Machine Learning},
author = {Jiahui Ma and Elizabeth Johnson and Bradley M. Whitaker and Faraz Dadgostari and Hansjorg Schwertz and Bernadette McCrory},
year = {2026},
journal = {Informatics},
doi = {10.3390/informatics13040047},
url = {https://doi.org/10.3390/informatics13040047}
}RIS
TY - JOUR TI - Concurrent Prediction of Length of Stay, Mortality, and Total Charges in Patients with Acute Lymphoblastic Leukemia Using Continuous Machine Learning AU - Jiahui Ma AU - Elizabeth Johnson AU - Bradley M. Whitaker AU - Faraz Dadgostari AU - Hansjorg Schwertz AU - Bernadette McCrory PY - 2026 JO - Informatics DO - 10.3390/informatics13040047 UR - https://doi.org/10.3390/informatics13040047 ER -
APA
Ma, J., Johnson, E., Whitaker, B. M., Dadgostari, F., Schwertz, H., & McCrory, B. (2026). Concurrent Prediction of Length of Stay, Mortality, and Total Charges in Patients with Acute Lymphoblastic Leukemia Using Continuous Machine Learning. Informatics. https://doi.org/10.3390/informatics13040047
Source records
- crossref · retrieved 2026-09-26T00:04:54.093Z