Artificial intelligence–derived oocyte morphology and follicular fluid biomarkers in donors

Yamila Herrero, Candela Velazquez, Melanie Neira, Romina Criscione, Mariano Lavolpe, Dalhia Abramovich, Fernanda Parborell

Open source

DOI
10.1093/reprod/xaag092
Published
2026-07-29
Container
Reproduction
Publisher
Oxford University Press (OUP)
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:10.1093/reprod/xaag092,
  title = {Artificial intelligence–derived oocyte morphology and follicular fluid biomarkers in donors},
  author = {Yamila Herrero and Candela Velazquez and Melanie Neira and Romina Criscione and Mariano Lavolpe and Dalhia Abramovich and Fernanda Parborell},
  year = {2026},
  journal = {Reproduction},
  doi = {10.1093/reprod/xaag092},
  url = {https://doi.org/10.1093/reprod/xaag092}
}

RIS

TY  - JOUR
TI  - Artificial intelligence–derived oocyte morphology and follicular fluid biomarkers in donors
AU  - Yamila Herrero
AU  - Candela Velazquez
AU  - Melanie Neira
AU  - Romina Criscione
AU  - Mariano Lavolpe
AU  - Dalhia Abramovich
AU  - Fernanda Parborell
PY  - 2026
JO  - Reproduction
DO  - 10.1093/reprod/xaag092
UR  - https://doi.org/10.1093/reprod/xaag092
ER  - 

APA

Herrero, Y., Velazquez, C., Neira, M., Criscione, R., Lavolpe, M., Abramovich, D., & Parborell, F. (2026). Artificial intelligence–derived oocyte morphology and follicular fluid biomarkers in donors. Reproduction. https://doi.org/10.1093/reprod/xaag092

Source records