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Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.

Sangwon BaekYeon-Joo JeongYun Hyeon KimJin Young KimJin Hwan KimEun Young KimJae-Kwang KimJungok KimZero KimKyunga KimMyung Jin Chung
Published in: Journal of medical Internet research (2024)
RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.
Keyphrases
  • end stage renal disease
  • clinical practice
  • ejection fraction
  • newly diagnosed
  • prognostic factors
  • coronavirus disease
  • peritoneal dialysis
  • sars cov