Machine Learning Models Versus the National Early Warning Score System for Predicting Deterioration: Retrospective Cohort Study in the United Arab Emirates.

Journal: JMIR AI
Published Date:

Abstract

BACKGROUND: Early warning score systems are widely used for identifying patients who are at the highest risk of deterioration to assist clinical decision-making. This could facilitate early intervention and consequently improve patient outcomes; for example, the National Early Warning Score (NEWS) system, which is recommended by the Royal College of Physicians in the United Kingdom, uses predefined alerting thresholds to assign scores to patients based on their vital signs. However, there is limited evidence of the reliability of such scores across patient cohorts in the United Arab Emirates.

Authors

  • Hazem Lashen
    Engineering Division, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Terrence Lee St John
    Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Y Zaki Almallah
    Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates.
  • Madhu Sasidhar
    Cleveland Clinic Tradition Hospital, Port St. Lucie, FL, United States.
  • Farah E Shamout
    Engineering Division, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.

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