
Artificial intelligence-driven tools are improving embryo selection for IVF by making health assessment more consistent and precise.
Key Details
- 1Approximately 17.5% of adult couples globally are affected by infertility, with IVF success rates averaging around 30%.
- 2Traditional embryo health assessments in IVF rely on subjective visual evaluations by embryologists.
- 3Recent AI advances enable automated analysis of embryo morphology images, reducing subjectivity and improving consistency.
- 4AI-driven approaches include deep learning applied to early, blastocyst, and full developmental stages using multimodal data.
- 5The review analyzed 37 studies and found AI often outperformed manual assessments in accuracy and efficiency.
- 6Challenges discussed include clinical integration, data quality, and ethical considerations.
Why It Matters

Source
EurekAlert
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