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Prediction of COVID-19 severity using laboratory findings on admission: informative values, thresholds, ML model performance.

Yauhen StatsenkoFatmah Al ZahmiTetiana HabuzaKlaus Neidl-Van GorkomNazar Zaki
Published in: BMJ open (2021)
The performance of the neural network trained with top valuable tests (aPTT, CRP and fibrinogen) is admissible (area under the curve (AUC) 0.86; 95% CI 0.486 to 0.884; p<0.001) and comparable with the model trained with all the tests (AUC 0.90; 95% CI 0.812 to 0.902; p<0.001). Free online tool at https://med-predict.com illustrates the study results.
Keyphrases
  • neural network
  • coronavirus disease
  • sars cov
  • resistance training
  • emergency department
  • social media
  • healthcare
  • health information