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Supervised learning for infection risk inference using pathology data.

Bernard HernandezPau HerreroTimothy Miles RawsonLuke S P MooreBenjamin EvansChristofer ToumazouAlison H HolmesPantelis Georgiou
Published in: BMC medical informatics and decision making (2017)
The selected biomarkers comprise enough information to perform infection risk inference with a high degree of confidence even in the presence of incomplete and imbalanced data. Since they are commonly available in hospitals, Clinical Decision Support Systems could benefit from these findings to assist clinicians in deciding whether or not to initiate antimicrobial therapy to improve prescription practices.
Keyphrases
  • electronic health record
  • clinical decision support
  • healthcare
  • big data
  • single cell
  • primary care
  • machine learning
  • staphylococcus aureus
  • palliative care
  • stem cells
  • data analysis
  • breast cancer risk