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An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential
Blastocyst selection is primarily based on morphological scoring systems and morphokinetic data. These methods involve subjective grading and time-consuming techniques. Artificial intelligence allows for objective and quick blastocyst selection. In this study, 608 blastocysts were selected for trans...
Autores principales: | Fruchter-Goldmeier, Yael, Kantor, Ben, Ben-Meir, Assaf, Wainstock, Tamar, Erlich, Itay, Levitas, Eliahu, Shufaro, Yoel, Sapir, Onit, Har-Vardi, Iris |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480200/ https://www.ncbi.nlm.nih.gov/pubmed/37669976 http://dx.doi.org/10.1038/s41598-023-40923-x |
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