Prediction of uterine cavity conception environment using two-dimensional transvaginal ultrasound imaging semantic feature-based machine learning: a case-control study
Machine learning models using semantic features derived from two-dimensional TVUS images enabled accurate preliminary screening for natural conception preparation or before embryo implantation.
Authors
- Suzhen Ran (ORCID: https://orcid.org/0000-0003-4545-9408)
- Peng Tu
- Jiyun Zhang (ORCID: https://orcid.org/0009-0000-0961-1084)
- Chunyan Zhong
- Rong Yue
- Shuang Liu (ORCID: https://orcid.org/0000-0002-0085-1644)
- Shangqing Liu (ORCID: https://orcid.org/0000-0003-1883-8090)
- Xiaohang Zhang (ORCID: https://orcid.org/0000-0002-5315-8712)
Institutions
- Chongqing Maternal and Child Health Hospital (CN)
- Children's Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Pregnancy and Childbirth
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1186/s12884-025-08390-6
- Primary Topic
- Gynecological conditions and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Chongqing
- Centre Scientifique et Technique du Bâtiment