Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions
- 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
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uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
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
- crossref · retrieved 2026-09-26T05:49:17.405Z