It takes one to know one-Machine learning for identifying OBGYN abstracts written by ChatGPT.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Published Date: Jan 17, 2024

Abstract

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.

Authors

  • Gabriel Levin
    Obstetrics & Gynecology Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.
  • Raanan Meyer
    Division of Minimally Invasive Gynecologic Surgery, Department of Obstetrics and Gynecology, Cedars Sinai Medical Center, Los Angeles, California, USA.
  • Paul-Adrien Guigue
    Lady Davis Institute for Cancer Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada.
  • Yoav Brezinov
    Department of Experimental Surgery, McGill University, Montreal, Quebec, Canada.

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