The Performance of 6 Commercial AI Algorithms in Stratifying the Risk of Embryo Ploidy – RBMO
Reproductive BioMedicine Online (RBMO) shared a post on LinkedIn about a paper by Carla Giménez-Rodríguez et al.։
“This study analyses the performance of six commercial AI algorithms in stratifying the risk of embryo ploidy.
Across 1000 PGT-A-validated blastocysts, although only one system was developed explicitly for ploidy prediction, all algorithms displayed a similar pattern of euploidy enrichment across higher score strata.
This suggests that AI-based embryo assessment captures morphological or developmental features modestly associated with chromosomal status, even when ploidy was not the primary training objective.
Authors Carla Giménez Rodríguez, Blanca Valdés Caparrós, Lorena Bori Arnal, PhD, Jose Bellver, José Alejandro Remohí, and Marcos Meseguer Escrivá say that, while these models do not offer diagnostic accuracy and should not replace genetic testing, AI scores may support embryo prioritization when PGT-A is not feasible, particularly in contexts where genetic testing is unavailable or contraindicated.
These findings suggest the existence of a shared performance ceiling across current AI approaches, and highlight the need for cautious, context-aware integration of AI into clinical embryo selection strategies.
The full paper is available to RBMO subscribers from the Clinical Embryology section of our October issue, now.”
Title: Head-to-head comparison of six commercial artificial intelligence algorithms for embryo ploidy risk stratification in 1000 PGT-A-tested blastocysts.
Authors: Carla Giménez Rodríguez, Blanca Valdés Caparrós, Lorena Bori Arnal, Jose Bellver, José Alejandro Remohí, Marcos Meseguer Escrivá.
You can read the Full Article in RBMO.
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