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Vital sign measurements demonstrate terminal digit bias and boundary effects.

Oliver KleinigMinh-Son ToChristopher D OvendenJoshua G KovoorRudy GohLydia LamTara WenzelYiran TanHrishikesh HarishAashray K GuptaSam GluckToby GilbertStephen Bacchi
Published in: Emergency medicine Australasia : EMA (2024)
Although often considered objective, vital signs data are affected by bias. These biases may impact the care patients receive. Additionally, it may have implications for creating and training machine learning models that utilise vital signs data.
Keyphrases
  • machine learning
  • end stage renal disease
  • big data
  • healthcare
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • peritoneal dialysis
  • prognostic factors
  • palliative care
  • quality improvement
  • patient reported