Embryo Selection in Assisted Reproduction: From Morphology to Artificial Intelligence

Embryo selection is a pivotal aspect of the field of assisted reproductive technology (ART), significantly impacting implantation potential, pregnancy success rates, and overall live birth outcomes. Traditionally, embryologists have relied on static morphological criteria or time-lapse imaging to identify embryos most likely to lead to successful pregnancies. However, as success rates remain suboptimal and inter-observer variability persists, there is growing demand for more objective and reproducible approaches. The introduction of artificial intelligence (AI), machine learning algorithms, and multi-omics data has sparked renewed debate regarding the best standards for embryo evaluation. While technological advances have enabled the capture and analysis of vast datasets, there remains substantial uncertainty around how best to define and identify embryo viability.Recent studies have demonstrated the potential for AI-driven tools to enhance prediction of embryonic development and implantation, utilizing morphokinetics, imaging data, and even non-invasive biomarkers. These systems show promise in offering more consistent and data-driven recommendations compared to conventional morphological grading. Notwithstanding these promising developments, key challenges endure: questions of ethical responsibility, algorithmic transparency, and clinical interpretability continue to shape the conversation. A lack of consensus persists regarding the integration of AI, whether as a complement or a replacement for traditional assessment, and the risk of introducing novel biases or overlooking nuanced biological insights remains.This Research Topic aims to offer an integrated and critical overview of current and next-generation approaches for embryo selection in ART, with a special focus on how technology, biology, and clinical application intersect. The goal is to foster multidisciplinary dialogue among practitioners, researchers, and ethicists to address unresolved questions, evaluate the comparative efficacy of various techniques, and outline practical, ethical, and regulatory frameworks for future standards.To gather further insights in the evolving practice and policy environment of embryo selection in ART, we welcome articles addressing, but not limited to, the following themes:o Comparative evaluation of morphological, morphokinetic, and AI-based assessment methodso Standards and challenges for clinical validation and generalizability of novel selection technologieso The role of non-invasive biomarkers and multi-omics in embryo viability predictiono Interpretability, transparency, and ethical concerns in AI-driven embryo selectiono Perspectives on how technological advances are reshaping professional roles and patient-centred careWe encourage the submission of Clinical Trial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Policy and Practice Reviews, Review, Study Protocol, Systematic Review, Technology and Code. Topic editors: Rocio Núñez Calonge, Sergio Novo Bruña Source: https://www.frontiersin.org/research-topics/78045/embryo-selection-in-assisted-reproduction-from-morphology-to-artificial-intelligence