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
AI tools in embryo imaging can standardize and improve IVF outcomes, minimizing variability between embryologists. The findings underscore the potential for imaging AI to set new benchmarks for precision and reliability in reproductive medicine.
Source
EurekAlert
Related News
•EurekAlert
AI and Advanced Microscopy Unveil Cell's Exocytosis Nanomachine
Researchers have discovered the ExHOS nanomachine responsible for constitutive exocytosis using advanced microscopy and AI-enhanced image analysis.
•EurekAlert
Physical Activity Linked to Breast Tissue Biomarkers in Teens
A study links adolescent recreational physical activity to changes in breast tissue composition and stress biomarkers, potentially impacting future breast cancer risk.
•EurekAlert
Deep Learning AI Outperforms Clinic Prognostics for Colorectal Cancer Recurrence
A new deep learning model using histopathology images identifies recurrence risk in stage II colorectal cancer more effectively than standard clinical predictors.