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Assessing Intensive Care Unit (ICU) Indications: Human vs. ChatGPT-4o Predictions

NCT06726733 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 624

Last updated 2026-04-14

No results posted yet for this study

Summary

This retrospective study evaluates the accuracy of ICU admission indications by comparing clinical decisions with predictions from ChatGPT-4. Patient data, including demographics, vital signs, laboratory results, imaging findings, and clinical decisions, will be retrospectively collected and documented systematically using Case Report Forms. The model will be trained using ICU admission guidelines and tasked to predict ICU needs based on collected patient data. This study aims to systematically assess the alignment between AI-based predictions and clinical decisions for ICU admissions.

Conditions

  • Intensive Care Unit (ICU) Admission
  • Emergency Department Patient
  • Artificial Intelligence (AI)
  • Clinical Decision-making

Sponsors & Collaborators

  • Bursa Yuksek Ihtisas Training and Research Hospital

    lead OTHER_GOV

Principal Investigators

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-01
Primary Completion
2024-11-30
Completion
2025-02-28

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06726733 on ClinicalTrials.gov