Artificial Intelligence in IVF: Can an Algorithm Choose the Best Embryo?
Artificial Intelligence in IVF has become a powerful ally for experienced fertility specialists, increasing the likelihood of a positive pregnancy test.
In vitro fertilization (IVF) is one of the most significant breakthroughs in assisted reproduction, offering hope to couples facing fertility challenges. In recent years, the integration of Artificial Intelligence (AI) into reproductive medicine has promised to enhance the process in both precision and success. This technology is paving the way for more personalized treatments, better outcome predictions, and optimization at every stage of the IVF journey.
How AI Supports the IVF Process
Embryo Analysis
One of the most critical stages in IVF is selecting the best embryo for transfer. Traditionally, this decision has relied on the embryologist’s experience and morphological assessment under a microscope. AI is transforming this approach: machine learning algorithms are trained on thousands of embryo images and can identify subtle features associated with higher implantation potential and successful pregnancy.
With technologies like time-lapse imaging, AI can monitor embryo development in real time and assess which embryos have the highest likelihood of leading to a viable pregnancy — often with greater accuracy than human observation alone.
Predictive Models for Treatment Outcomes
AI is also being used to forecast treatment success based on medical history, hormone levels, egg and sperm quality, and previous IVF attempts. This allows fertility doctors to tailor medication and ovarian stimulation protocols more effectively, increasing the odds of success while reducing the number of failed cycles.
Decision Support
Fertility specialists make dozens of complex decisions during each IVF cycle. AI provides data-driven insights and predictions that support clinicians in choosing the optimal timing for egg retrieval, embryo transfer, or cryopreservation, while reducing the risk of subjective error.
Innovative AI Technologies in Assisted Reproduction in Greece
In recent years, AI in IVF has been at the forefront of research aiming to improve embryo selection and success rates. As a pioneer and industry leader, Institute of Life – IASO has been implementing state-of-the-art AI tools since 2023.
FOR EMBRYOS
- Chloe EQ (Fairtility) – Real-Time Embryo Monitoring and Assessment
Chloe EQ (Embryo Quality) is an advanced AI system designed to monitor and evaluate embryo quality in real time within time-lapse incubators.
How it works
Chloe EQ continuously tracks embryo development from fertilization to day 5 (blastocyst stage), recording each cell division, morphological change, and timing sequence.
Its algorithm analyzes this data to generate a predictive score for each embryo based on historical data and statistical models.
The embryologist can use this score to select the most promising embryo for transfer, thereby increasing the likelihood of successful pregnancy.
Chloe EQ provides full transparency and rationale for each assessment, empowering both doctors and couples to better understand their choices. Importantly, it serves as a complementary tool — supporting, not replacing, the embryologist’s expertise.
- Erica (AI 2.0) – Algorithmic Accuracy in Embryo Viability Prediction
Erica is part of the AI 2.0 platform, an advanced technology designed to predict the reproductive potential of embryos — in other words, their likelihood of successful implantation and development into pregnancy.
How it works
Erica analyzes morphokinetic data from embryo development as well as structural and dynamic cell quality indicators.
It draws on vast databases comprising hundreds of thousands of IVF cycles to identify which embryo characteristics statistically correlate with successful outcomes.
It provides a predictive model that helps personalize treatment — especially valuable in cases of recurrent failure or difficult infertility diagnoses.
Erica also serves as a powerful implantation prediction tool, enhancing embryo selection strategies.
- iDAScore (Vitrolife) – Fully Automated Embryo Evaluation Using Deep Learning
iDAScore is one of the most widely used automated AI systems developed by Vitrolife in collaboration with deep learning experts.
How it works
It requires no manual input from the embryologist. It relies solely on time-lapse images captured during embryo culture.
The algorithm scores each embryo based on its implantation potential, using data from over
100,000 IVF cycles.
Advantages:
Entirely objective assessment with no human bias
Reduces variability among embryologists, increasing consistency in embryo selection
Widely adopted in leading European and U.S. fertility clinics as a gold standard
FOR OOCYTES
Chloe OQ (Fairtility) – Algorithmic Precision in Oocyte Assessment
Chloe OQ is a specialized AI system designed exclusively for analyzing and scoring oocytes prior to freezing or fertilization. It incorporates a machine learning algorithm trained on large datasets from embryology labs and detects subtle morphological patterns invisible to the human eye.
How it works
During microscopic examination, Chloe OQ assesses both the outer morphology and dynamic characteristics of each oocyte, including cytoplasmic integrity, zona pellucida clarity, and presence of vacuoles.
It then assigns a score estimating the likelihood that the oocyte will develop into a viable day-5 embryo (blastocyst), thus reflecting its reproductive potential.
Chloe OQ makes the assessment process more objective, repeatable, and personalized, minimizing inter-embryologist variability. It is particularly useful for women preserving their fertility, offering scientifically grounded insights into the quality of the eggs being frozen.
FOR SPERM CELLS DURING ICSI
SiD (AI 2.0) – Revolutionary AI Sperm Selection for ICSI
SiD (Sperm Identification Device) is an emerging AI-powered technology aimed at selecting the best sperm for use in intracytoplasmic sperm injection (ICSI) — the direct injection of a single sperm into an egg.
How it works
SiD analyzes high-resolution video of sperm movement and morphology in real time under the microscope.
Using deep learning algorithms, it evaluates parameters such as motility, head symmetry, neck structure, and other microscopic quality indicators. Its goal is to identify the sperm with the highest probability of achieving successful fertilization and embryo development.
Although SiD is still undergoing clinical validation, early results suggest it may significantly boost IVF success rates — particularly in cases of male infertility or repeated IVF failure.
Institute of Life – IASO is the first and only fertility center in Greece to apply the Chloe OQ (Comprehensive Lab Ovum Evaluation) system. This enables women undergoing fertility preservation to make more informed decisions about their reproductive future, grounded in objective data and with greater confidence. It is also the only AI system in Europe to offer such detailed and personalized predictions regarding embryo viability. Moreover, it is proving to be especially valuable for women with a history of failed embryo transfers or miscarriages, as it allows for assessment of oocyte quality before fertilization even occurs.
Conclusion
AI does not replace the fertility specialist or the embryologist — it empowers them. As AI-driven fertility treatments become more personalized, we may be moving toward a future where customized IVF protocols are the norm rather than the exception.
With skilled clinicians, ethical oversight, and a commitment to transparency, Artificial Intelligence could revοlutionize IVF and help even more people achieve parenthood.
Τhe final responsibility for any medical decision lies with the healthcare provider. AI may guide — but it cannot decide in ethical or emotional terms, especially in a field as sensitive and human as assisted reproduction.
