The American journal of emergency medicine
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Comparative Study
Comparison of emergency medicine specialist, cardiologist, and chat-GPT in electrocardiography assessment.
ChatGPT, developed by OpenAI, represents the cutting-edge in its field with its latest model, GPT-4. Extensive research is currently being conducted in various domains, including cardiovascular diseases, using ChatGPT. Nevertheless, there is a lack of studies addressing the proficiency of GPT-4 in diagnosing conditions based on Electrocardiography (ECG) data. The goal of this study is to evaluate the diagnostic accuracy of GPT-4 when provided with ECG data, and to compare its performance with that of emergency medicine specialists and cardiologists. ⋯ Our study has shown that GPT-4 is more successful than emergency medicine specialists in evaluating both everyday and more challenging ECG questions. It performed better compared to cardiologists on everyday questions, but its performance aligned closely with that of the cardiologists as the difficulty of the questions increased.
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To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation. ⋯ We developed and validated models to identify suspected serious infection in the ED. Extracted information from initial ED physician notes using NLP contributed to increased model performance, permitting identification of suspected serious infection at early stages of ED visits.
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To characterize the clinical features of ocular trauma resulting from lawn mower, identify determinants of unfavorable final visual acuity (FVA), and assess the spectrum of microbial in posttraumatic endophthalmitis. ⋯ Lawn mower often cause severe ocular injuries, with high-velocity metal foreign bodies that can lead to infections, most commonly caused by Bacillus cereus. Correct use of protective gear, initial vision assessment, and detecting retinal detachment are crucial for visual prognosis.
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Compared to conventional cardiac troponin (cTn), the high-sensitivity cardiac troponin (hs-cTn) assay is associated with improved detection of myocardial infarction (MI). ⋯ Transitioning from cTn to hs-cTn was associated with significantly increased ED discharges and an increase in troponin tests, ECG, echocardiograms, and coronary angiograms. There was a decrease in the number of stress tests.