Artificial Intelligence

We use AI in IVF in the following key areas to help you find the solution that suits you best:

• Embryo Selection: One of the most significant challenges in IVF is identifying the most viable embryos for transfer. AI algorithms analyse a multitude of data points, including embryo morphology, developmental kinetics, and genetic information, to predict embryo quality and implantation potential accurately. This enables embryologists to select the best embryos for transfer, leading to higher pregnancy rates and reduced miscarriage rates.

• Predictive Analytics: AI-based predictive models leverage patient-specific data, such as age, ovarian reserve, hormone levels, and previous treatment outcomes, to forecast the likelihood of IVF success. By identifying factors that may impact treatment outcomes, clinicians can tailor treatment protocols and interventions to optimise chances of conception and live birth.

• Ovarian Response Prediction: AI algorithms can predict a patient's ovarian response to stimulation protocols, allowing for the optimization of medication dosages and treatment strategies. This personalized approach minimizes the risk of ovarian hyperstimulation syndrome (OHSS) and maximizes the chances of retrieving an adequate number of high-quality eggs for fertilization.

• Time-Lapse Imaging: Time-lapse imaging systems, integrated with AI algorithms, continuously monitor embryo development in real-time, capturing thousands of images to assess embryo morphology and kinetics. AI-based analysis provides valuable insights into embryo viability, allowing embryologists to make informed decisions regarding embryo selection and transfer.

• Genetic Screening: AI-driven genetic screening techniques, such as preimplantation genetic testing (PGT), analyse vast genomic data to identify chromosomal abnormalities and genetic disorders in embryos. This enables the selection of genetically normal embryos, reducing the risk of inherited diseases and improving the success of IVF treatment.