@article{10938,
  keywords = {Humans, *Electronic Health Records, Unsupervised Machine Learning, England/epidemiology, Hospitalization, *Acute Kidney Injury/epidemiology/diagnosis, Acute kidney injury, Clustering, Phenotypes, Seasonality},
  author = {H. Bolt and A. Suffel and J. Matthewman and F. Sandmann and L. Tomlinson and R. Eggo},
  title = {Seasonality of acute kidney injury phenotypes in England: an unsupervised machine learning classification study of electronic health records},
  year = {2023},
  journal = {BMC Nephrol},
  volume = {24},
  edition = {2023/08/10},
  number = {1},
  pages = {234},
  isbn = {1471-2369},
  doi = {10.1186/s12882-023-03269-0},
  note = {1471-2369
Bolt, Hikaru
Suffel, Anne
Matthewman, Julian
Sandmann, Frank
Tomlinson, Laurie
Eggo, Rosalind
DH_/Department of Health/United Kingdom
Journal Article
Research Support, Non-U.S. Gov't
England
BMC Nephrol. 2023 Aug 9;24(1):234. doi: 10.1186/s12882-023-03269-0.},
  language = {eng},
}