• Farrokh Habibzadeh.
• Past President, World Association of Medical Editors (WAME), Editorial Consultant, The Lancet, Associate Editor, Frontiers in Epidemiology. Farrokh.Habibzadeh@gmail.com.
• J. Korean Med. Sci. 2023 Sep 25; 38 (38): e319e319.

BackgroundWith emergence of chatbots to help authors with scientific writings, editors should have tools to identify artificial intelligence-generated texts. GPTZero is among the first websites that has sought media attention claiming to differentiate machine-generated from human-written texts.MethodsUsing 20 text pieces generated by ChatGPT in response to arbitrary questions on various topics in medicine and 30 pieces chosen from previously published medical articles, the performance of GPTZero was assessed.ResultsGPTZero had a sensitivity of 0.65 (95% confidence interval, 0.41-0.85); specificity, 0.90 (0.73-0.98); accuracy, 0.80 (0.66-0.90); and positive and negative likelihood ratios, 6.5 (2.1-19.9) and 0.4 (0.2-0.7), respectively.ConclusionGPTZero has a low false-positive (classifying a human-written text as machine-generated) and a high false-negative rate (classifying a machine-generated text as human-written).© 2023 The Korean Academy of Medical Sciences.

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