Machine Learning Identification of Genetic Variants Associated with Sub-Optimal Ovarian Response and Hyper-Response
The present study has identified 6 polymorphisms associated with variability in response to ovarian stimulation in young women with good ovarian reserve indicators using machine learning. Women who carry these genetic variants may be suitable candidates for personalised ovarian stimulation treatments to help prevent inadequate responses.
Authors
- Jaime Guerrero (ORCID: https://orcid.org/0000-0002-6097-2691)
- José Antonio Ortiz (ORCID: https://orcid.org/0000-0003-0505-3032)
- Belén Lledó (ORCID: https://orcid.org/0000-0002-3583-7893)
- Andrea Bernabeu (ORCID: https://orcid.org/0000-0002-9427-6360)
- R Morales
- Lydia Luque
Institutions
- Instituto Bernabeu (ES)
Publication Details
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1109/cbms65348.2025.00108
- Citations
- 1
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 1.82