Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions

Jianye Wang, Zhicheng Jia, Keliang Wu, Penglin Liu, Jiale Du, Li Li

Open source

DOI
10.1007/s10815-026-04006-w
Published
2026-09-10
Container
Journal of Assisted Reproduction and Genetics
Publisher
Springer Science and Business Media LLC
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1007/s10815-026-04006-w,
  title = {Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions},
  author = {Jianye Wang and Zhicheng Jia and Keliang Wu and Penglin Liu and Jiale Du and Li Li},
  year = {2026},
  journal = {Journal of Assisted Reproduction and Genetics},
  doi = {10.1007/s10815-026-04006-w},
  url = {https://doi.org/10.1007/s10815-026-04006-w}
}

RIS

TY  - JOUR
TI  - Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions
AU  - Jianye Wang
AU  - Zhicheng Jia
AU  - Keliang Wu
AU  - Penglin Liu
AU  - Jiale Du
AU  - Li Li
PY  - 2026
JO  - Journal of Assisted Reproduction and Genetics
DO  - 10.1007/s10815-026-04006-w
UR  - https://doi.org/10.1007/s10815-026-04006-w
ER  - 

APA

Wang, J., Jia, Z., Wu, K., Liu, P., Du, J., & Li, L. (2026). Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions. Journal of Assisted Reproduction and Genetics. https://doi.org/10.1007/s10815-026-04006-w

Source records