Enhancing trainee performance in obstetric ultrasound through an artificial intelligence system: randomized controlled trial
By assisting inexperienced trainees in obtaining and interpreting standard basic obstetric scanning views, the use of artificial intelligence-assisted systems has the potential to improve training effectiveness. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.
Authors
- Hongning Xie (ORCID: https://orcid.org/0000-0002-1705-1328)
- Qian Zhou (ORCID: https://orcid.org/0000-0003-3954-5449)
- Min-Huei Lin
- Linzhe Zhang
- Ting Lei (ORCID: https://orcid.org/0000-0001-7911-2264)
- M. He (ORCID: https://orcid.org/0009-0005-9930-2387)
- Qiao Zheng (ORCID: https://orcid.org/0000-0002-3040-2137)
- Jianxing Feng (ORCID: https://orcid.org/0000-0002-4180-3323)
Institutions
- Sun Yat-sen University (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
Publication Details
- Journal
- Ultrasound in Obstetrics and Gynecology
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1002/uog.29101
- Citations
- 12
- Primary Topic
- Ultrasound in Clinical Applications
- Type
- article
- Field-Weighted Citation Impact
- 5.06
Funders
- Sun Yat-sen University
- National Key Research and Development Program of China