A machine learning–assisted approach to explain key determinants for achieving live birth in autologous ICSI cycles
- DOI
- 10.1007/s10815-026-03869-3
- Published
- 2026-04-14
- Container
- Journal of Assisted Reproduction and Genetics
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s10815-026-03869-3,
title = {A machine learning–assisted approach to explain key determinants for achieving live birth in autologous ICSI cycles},
author = {Juan J. Fraire-Zamora and Nuria Correa and Karinna Lattes and Mina Popovic and Amelia Rodriguez-Aranda},
year = {2026},
journal = {Journal of Assisted Reproduction and Genetics},
doi = {10.1007/s10815-026-03869-3},
url = {https://doi.org/10.1007/s10815-026-03869-3}
}RIS
TY - JOUR TI - A machine learning–assisted approach to explain key determinants for achieving live birth in autologous ICSI cycles AU - Juan J. Fraire-Zamora AU - Nuria Correa AU - Karinna Lattes AU - Mina Popovic AU - Amelia Rodriguez-Aranda PY - 2026 JO - Journal of Assisted Reproduction and Genetics DO - 10.1007/s10815-026-03869-3 UR - https://doi.org/10.1007/s10815-026-03869-3 ER -
APA
Fraire-Zamora, J. J., Correa, N., Lattes, K., Popovic, M., & Rodriguez-Aranda, A. (2026). A machine learning–assisted approach to explain key determinants for achieving live birth in autologous ICSI cycles. Journal of Assisted Reproduction and Genetics. https://doi.org/10.1007/s10815-026-03869-3
Source records
- crossref · retrieved 2026-09-26T10:11:29.783Z