AI-based analysis of embryo morphokinetics for predicting embryo viability and ploidy: A literature review
DOI:
https://doi.org/10.37800/RM.3.2026.795Keywords:
Embryo morphokinetics, artificial intelligence (AI), in vitro fertilization (IVF), preimplantation genetic testing (PGT-A), embryo viability, Time-Lapse, iDAScoreAbstract
Relevance: Embryo selection remains an essential component of assisted reproductive technology (ART) and plays a vital role in successful implantation and subsequent pregnancy. Standard morphological evaluation is inherently subjective and highly variable among observers. Time-lapse systems, together with artificial intelligence (AI), have been identified as potentially useful modalities that can increase the accuracy and reliability of embryo evaluation. In particular, the use of AI in analyzing embryo morphokinetics has received considerable attention.
The study aimed to discuss current findings embryo viability and ploidy in in vitro fertilization (IVF) treatment programs.
Materials and Methods: Articles published between 2014 and 2026 were reviewed in the literature. We conducted the review using the PubMed, Scopus, Web of Science, Google Scholar, and ScienceDirect databases, with keywords such as AI, morphokinetics, time-lapse imaging, embryo viability, and aneuploidy. We included original articles, systematic reviews, meta-analyses, and clinical studies. All graphs used in this review were created in BioRender.
Results: Strong associations were established between morphokinetic parameters and embryo quality, implantation potential, and ploidy status. Machine learning and deep learning algorithms have been shown to analyze embryo development processes more objectively than traditional morphological evaluations. Several studies have demonstrated the potential of AI-based techniques to improve the prediction of aneuploidy risk and embryo viability. Nevertheless, important limitations remain before these approaches can be widely adopted in clinical practice. Conclusion: AI-assisted embryo evaluation is a useful technology in personalized reproductive medicine. Standardization and further multicenter validation studies are needed before its routine use in ART clinics.
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