Predicting Mortality in Hospitalized COVID‐19 Patients in Zambia: An Application of Machine Learning

Clyde Mulenga, Patrick Kaonga, Raymond Hamoonga, Mazyanga Lucy Mazaba, Freeman Chabala, Patrick Musonda

Open source

DOI: 10.1155/2023/8921220
Published: 2023-01
Container: Global Health, Epidemiology and Genomics
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1155/2023/8921220,
  title = {Predicting Mortality in Hospitalized COVID‐19 Patients in Zambia: An Application of Machine Learning},
  author = {Clyde Mulenga and Patrick Kaonga and Raymond Hamoonga and Mazyanga Lucy Mazaba and Freeman Chabala and Patrick Musonda},
  year = {2023},
  journal = {Global Health, Epidemiology and Genomics},
  doi = {10.1155/2023/8921220},
  url = {https://doi.org/10.1155/2023/8921220}
}

RIS

TY  - JOUR
TI  - Predicting Mortality in Hospitalized COVID‐19 Patients in Zambia: An Application of Machine Learning
AU  - Clyde Mulenga
AU  - Patrick Kaonga
AU  - Raymond Hamoonga
AU  - Mazyanga Lucy Mazaba
AU  - Freeman Chabala
AU  - Patrick Musonda
PY  - 2023
JO  - Global Health, Epidemiology and Genomics
DO  - 10.1155/2023/8921220
UR  - https://doi.org/10.1155/2023/8921220
ER  -

APA

Mulenga, C., Kaonga, P., Hamoonga, R., Mazaba, M. L., Chabala, F., & Musonda, P. (2023). Predicting Mortality in Hospitalized COVID‐19 Patients in Zambia: An Application of Machine Learning. Global Health, Epidemiology and Genomics. https://doi.org/10.1155/2023/8921220

Source records

crossref · retrieved 2026-09-26T06:53:42.904Z