首页|Studies from Ankara Bilkent City Hospital Provide New Data on Artificial Intelli gence (Emergency department triaging using Chat- GPT based on emergency severity i ndex principles: a cross-sectional study)
Studies from Ankara Bilkent City Hospital Provide New Data on Artificial Intelli gence (Emergency department triaging using Chat- GPT based on emergency severity i ndex principles: a cross-sectional study)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news originating from the Ankara Bilkent City Hospital by NewsRx editors, the research stated, “Erroneous and del ayed triage in an increasingly crowded emergency department (ED). ChatGPT is an artificial intelligence model developed by OpenAI® and is being trained for use in natural language processing tasks.” Our news journalists obtained a quote from the research from Ankara Bilkent City Hospital: “Our study aims to determine the accuracy of patient triage using Cha tGPT according to the emergency severity index (ESI) for triage in EDs. In our c ross-sectional study, 18 years and over patients who consecutively presented to our ED within 24 h were included. Age, gender, admission method, chief complaint , state of consciousness, and comorbidities were recorded on the case form, and the vital signs were detected at the triage desk. A five-member expert committee (EC) was formed from the fourth-year resident physicians. The investigators con verted real-time patient information into a standardized case format. The urgenc y status of the patients was evaluated simultaneously by EC and ChatGPT accordin g to ESI criteria. The median value of the EC decision was accepted as the gold standard. There was a statistically significant moderate agreement between EC an d ChatGPT assessments regarding urgency status (Cohen’s Kappa = 0.659; P <0.001). The accuracy between these two assessments was calculated as 76.6% . There was a high degree of agreement between EC and ChatGPT for the prediction of ESI-1 and 2, indicating high acuity (Cohen’s Kappa = 0.828). The diagnostic specificity, NPV, and accuracy of ChatGPT were determined as 95.63, 98.17 and 94 .90%, respectively, for ESI high acuity categories.”
Ankara Bilkent City HospitalArtificial IntelligenceEmerging TechnologiesMachine Learning
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