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IVF has given many couples the opportunity to build their families. However, the journey to conception through IVF isn't always smooth sailing—often, the challenge is choosing the right embryo to implant. In this area, artificial intelligence (AI) is on the verge of revolutionizing the way embryo selection processes take place and providing more precise, objective scoring of embryos. In this article, we take a look at how AI is changing embryo selection and helping to boost IVF success rates.
Machine learning algorithms are used in AI-based embryo selection to analyze embryo images and provide scores indicating the probability of successful implantation. Embryologists have traditionally assessed embryos using the Gardner score, which is based on the morphology and blastocyst expansion of the embryo and the quality of the inner cell mass (ICM) and trophectoderm (TE). Built on these factors, AI embryo scoring uses advanced imaging and data analysis to increase accuracy and efficiency.
Then AI systems are trained on thousands of embryo images with known outcomes and can learn how to identify complex patterns associated with embryo viability. In AI embryo scoring, the AI model generates an image of each embryo and scores them on a number of characteristics that may not be apparent to the human eye alone. The AI score values range from 0 (least viable) to 10 (most viable) so that embryologists know which embryos to transfer, freeze, or continue to analyze.
The use of AI models gives a standardized, highly accurate scoring system that reduces the risk of human error. AI scoring is 27.9% more accurate at predicting pregnancy outcomes than traditional Gardner scoring in studies.
AI-based embryo selection can potentially reduce the number of IVF cycles, reducing the cost and emotional toll on patients, by selecting the most viable embryos in fewer attempts.
The AI model’s algorithm provides a standardized assessment, which removes the subjectivity of manual grading methods, where the assessment is dependent on the experience of the embryologist.
Gardner is an established scoring method for grading embryos by expansion grade, ICM grade, and TE grade. This method may be effective but is subjective and misses some of the details of embryo viability. However, AI embryo scoring is able to analyze morphological features that may fall beyond human observation, such as blastocyst development and structural quality. In fact, studies show that AI’s ability to detect more nuanced differences correlates well with pregnancy outcomes, with an accuracy of 49.8% for predicting success rates versus Gardner’s 39.0%.
AI-based embryo selections are one of the significant advancements in the IVF journey of patients. However, it does not come without limitations and considerations. For example, the effectiveness of AI scoring depends on a lot of factors, which include the quality of imagining and the breadth of the training data. AI models continue to evolve and therefore there is still ongoing research and development to verify the scoring accuracy.
The future of reproductive medicine is going to be AI-based embryo selection, which will allow for more successful and accessible IVF treatments. When the technology matures, we can expect increased accuracy of scoring, reduced cost, and improved patient outcomes. AI-enhanced embryo selection is an exciting step forward for individuals and couples looking to realize the dream of parenthood.
AI-based embryo selection is a powerful tool for patients and fertility specialists alike. AI scoring provides a more objective, more precise, and more data-driven approach, hence reducing the number of IVF cycles and increasing the chances of a successful pregnancy.
If you are considering IVF and want to explore the benefits of AI-based embryo selection, then Maaeri is here to help you. We are committed to providing you with the latest in fertility technology and more. Just give us a call to book your consultation now.
