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This article compares the use of ChatGPT, an artificial intelligence language model, with Google Search and institutional sources for providing postoperative patient instructions after gynecological surgery. The study analyzed instructions for five common procedures and evaluated their understandability and actionability using the Patient Education Materials Assessment Tool. The results showed that ChatGPT provided concise instructions with similar understandability scores compared to the other sources, but lower actionability scores and less information on concerning signs and symptoms. The study concludes that while ChatGPT can offer tailored responses, it may compromise patient safety by lacking specific actionable items and important instructions. [Extracted from the article]

A systematic review and meta-analysis was conducted to assess the performance of ChatGPT, an artificial intelligence language model, in medical examinations. The study analyzed 19 articles that reported ChatGPT's performance in various medical fields, such as plastic surgery, anesthesia, and diabetes. The overall performance of ChatGPT ranged from 40% to 100%, with a mean performance of 61.1%. The study suggests that ChatGPT has the potential to be a useful educational tool in medical education, but caution should be exercised in its use for examination preparation. Future research is needed to explore the role of AI chatbots in medical education. [Extracted from the article]

Objectives: To use machine learning to optimize the detection of obstetrics and gynecology (OBGYN) Chat Generative Pre‐trained Transformer (ChatGPT) ‐written abstracts of all OBGYN journals. Methods: We used Web of Science to identify all original articles published in all OBGYN journals in 2022. Seventy‐five original articles were randomly selected. For each, we prompted ChatGPT to write an abstract based on the title and results of the original abstracts. Each abstract was tested by Grammarly software and reports were inserted into a database. Machine‐learning modes were trained and examined on the database created. Results: Overall, 75 abstracts from 12 different OBGYN journals were randomly selected. There were seven (58%) Q1 journals, one (8%) Q2 journal, two (17%) Q3 journals, and two (17%) Q4 journals. Use of mixed dialects of English, absence of comma‐misuse, absence of incorrect verb forms, and improper formatting were important prediction variables of ChatGPT‐written abstracts. The deep‐learning model had the highest predictive performance of all examined models. This model achieved the following performance: accuracy 0.90, precision 0.92, recall 0.85, area under the curve 0.95. Conclusions: Machine‐learning‐based tools reach high accuracy in identifying ChatGPT‐written OBGYN abstracts. Synopsis: Machine‐learning‐based tools reach high accuracy in identifying ChatGPT‐written obstetrics and gynecology abstracts. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the performance of ChatGPT in a French medical school entrance examination. Methods: A cross‐sectional study using a consecutive sample of text‐based multiple‐choice practice questions for the Parcours d'Accès Spécifique Santé. ChatGPT answered questions in French. We compared performance of ChatGPT in obstetrics and gynecology (OBGYN) and in the whole test. Results: Overall, 885 questions were evaluated. The mean test score was 34.0% (306; maximal score of 900). The performance of ChatGPT was 33.0% (292 correct answers, 885 questions). The performance of ChatGPT was lower in biostatistics (13.3% ± 19.7%) than in anatomy (34.2% ± 17.9%; P = 0.037) and also lower than in histology and embryology (40.0% ± 18.5%; P = 0.004). The OBGYN part had 290 questions. There was no difference in the test scores and the performance of ChatGPT in OBGYN versus the whole entrance test (P = 0.76 vs P = 0.10, respectively). Conclusions: ChatGPT answered one‐third of questions correctly in the French test preparation. The performance in OBGYN was similar. Synopsis: ChatGPT performance in French language medical tests is low. [ABSTRACT FROM AUTHOR]