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AI în medicina de urgență și test de triaj

Examinați datele și fluxurile de lucru ale AI pentru triaj de urgență, inclusiv etichetele rezultatelor, semnalele structurate, scorurile de avertizare timpurie bazate pe reguli și pragurile de alertă.

Căi de ghidare aferenteAI în medicina de urgență și triaj
Întrebare 1 de 8

What is the main purpose of emergency-department triage?

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  1. What is the main purpose of emergency-department triage?
    • Prioritize patients by urgency so those at greatest immediate risk are assessed first
    • Diagnose every patient before registration
    • Replace clinician judgment with an automated score
    • Determine insurance coverage before clinical assessment
  2. In the cited retrospective study, what input did machine learning use to recognize out-of-hospital cardiac arrest?
    • Satellite images of ambulance routes
    • Audio recordings of emergency calls
    • Only pharmacy claims
    • Hospital discharge summaries written after the event
  3. What did the cited prehospital AI-ECG study evaluate?
    • A model to predict water demand from weather
    • A speech system to transcribe patient histories
    • A CNN-LSTM model to classify STEMI from ambulance-acquired ECGs
    • A robot to perform catheterization without clinicians
  4. What does AHRQ mean by alert fatigue?
    • A patient becomes tired after an emergency alert
    • A triage nurse receives no patient information
    • A medical device battery stops charging
    • Clinicians become desensitized to frequent alerts and may ignore important ones
  5. Which inputs did the cited eCART Lite deterioration model use?
    • Patient age, heart rate and respiratory rate
    • Only free-text social-media posts
    • CT scans and genetic sequences only
    • Billing codes without vital signs
  6. What stage of AI clinical decision-support evaluation does DECIDE-AI provide a reporting guideline for?
    • Only simulation before any human use
    • Early-stage live clinical evaluation in real clinical workflows
    • Only retrospective model development with no clinical context
    • A universal authorization for automated treatment
  7. Which outcomes did the cited ED triage prediction study use?
    • Crop yield and soil moisture only
    • Insurance premiums and readmission penalties only
    • Critical care (ICU admission or in-hospital death) and hospitalization
    • Patient satisfaction and staff retention only
  8. Which conventional triage system did the cited machine-learning study use as its reference model?
    • The Montreal Cognitive Assessment
    • The Glasgow Coma Scale
    • NEWS2 as a radiology image model
    • The Emergency Severity Index (ESI)