Using machine-learning risk prediction models to triage the acuity of undifferentiated patients entering the emergency care system: a systematic review.
Jamie MilesJanette TurnerRichard JacquesJulia WilliamsSuzanne MasonPublished in: Diagnostic and prognostic research (2020)
This systematic review is registered on the International prospective register of systematic reviews (PROSPERO) and can be accessed online at the following URL: https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020168696This study was funded by the NIHR as part of a Clinical Doctoral Research Fellowship.
Keyphrases
- systematic review
- emergency department
- meta analyses
- end stage renal disease
- healthcare
- ejection fraction
- newly diagnosed
- palliative care
- chronic kidney disease
- public health
- peritoneal dialysis
- social media
- randomized controlled trial
- patient reported outcomes
- cross sectional
- pain management
- health information
- emergency medicine