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Response: Comparing letters written by humans and ChatGPT: A preliminary study.
Int J Gynaecol Obstet
January 2025
Department of Obstetrics and Gynecology, Jichi Medical University, Tochigi, Japan.
Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education.
BMC Med Educ
January 2025
Department of Urology, Xiangya Hospital, Central South University, Changsha, Hunan, 410000, China.
Introduction: Artificial intelligence technology has a wide range of application prospects in the field of medical education. The aim of the study was to measure the effectiveness of ChatGPT-assisted problem-based learning (PBL) teaching for urology medical interns in comparison with traditional teaching.
Methods: A cohort of urology interns was randomly assigned to two groups; one underwent ChatGPT-assisted PBL teaching, while the other received traditional teaching over a period of two weeks.
Regulation for ChatGPT use in paper writing.
Taiwan J Obstet Gynecol
January 2025
Department of Obstetrics and Gynecology, Jichi Medical University, Tochigi, Japan; Department of Obstetrics and Gynecology, Koga Red Cross Hospital, 1150 Shimoyama, Koga, Ibaraki 306-0014, Japan; Medical Examination Center, Ibaraki Western Medical Center, 555 Otsuka, Chikusei, Ibaraki 308-0813, Japan. Electronic address:
Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study.
JMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
View Article and Find Full Text PDFEmotional analysis of operating room nurses in acute care hospitals in Japan: insights using ChatGPT.
BMC Nurs
January 2025
Department of Healthcare Management Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan.
Aim: This study aimed to explore the emotions of operating room nurses in Japan towards perioperative nursing using generative AI and human analysis, and to identify factors contributing to burnout and turnover.
Methods: A single-center cross-sectional study was conducted from February 2023 to February 2024, involving semi-structured interviews with 10 operating room nurses from a national hospital in Japan. Interview transcripts were analyzed using generative AI (ChatGPT-4o) and human researchers for thematic, emotional, and subjectivity analysis.
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