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.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Accuracy rate of ChatGPT-4 in predicting ICU indications
Timeframe: 3 month
False positive rate
Timeframe: 3 month
False negative rate
Timeframe: 3 month