Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS).
Zhaoyi ChenVictoria Y BirdRupam RuchiMark S SegalJiang BianSaeed R KhanMarie-Carmelle ElieMattia ProsperiPublished in: BMC medical informatics and decision making (2018)
Although external validation is warranted, DACA-KS could be integrated into electronic health systems; the algorithm has the potential used as an effective tool to help nurses and healthcare personnel during triage or clinicians making a diagnosis, streamlining patients' management in acute care.
Keyphrases
- acute care
- healthcare
- end stage renal disease
- machine learning
- emergency department
- newly diagnosed
- deep learning
- chronic kidney disease
- ejection fraction
- peritoneal dialysis
- palliative care
- electronic health record
- prognostic factors
- patient reported outcomes
- artificial intelligence
- social media
- health information
- health insurance
- affordable care act
- clinical evaluation