Will artificial intelligence contribute to improving the success rates of IVF?

Overview of Ubar Technology

The Israeli company Embryonics, founded in 2018 in Haifa, has developed Ubar technology which, by analyzing the developmental data of embryos and using machine learning algorithms, allows for a more precise selection of the most promising embryos to be transferred into the uterus.

Advantages of Ubar Technology

According to the company, thanks to this technology, the accuracy of predicting the successful implantation of selected embryos has exceeded predictions by 20% from a group of embryologists, which has been confirmed by several comparative studies involving the analysis of prediction effectiveness with the participation of experienced specialists. Ubar technology has also proven to be 30% more accurate in identifying the least promising embryos for implantation. The designers of this technology claim that it will reduce the number of unsuccessful IVF attempts and help couples undergoing fertility treatment save money.

How Ubar Technology Works

Embryonics utilizes advancements in machine learning. Ubar technology was developed from data from tens of thousands of IVF cycles, including frame-by-frame videos of embryo development, to analyze each stage of embryo growth and identify subtle changes that may indicate embryo viability and implantation prospects. In addition to embryo selection, the company also uses this technology to select eggs that can be preserved for later use (deferred motherhood).

CEO's Opinion

Dr. Yael Zamir, the CEO of the company, stated that Ubar technology does not imitate a human expert but serves to enhance the level of precision during the procedure of selecting the most promising embryos before embryo transfer. Dr. Zamir indicated that this technology would improve IVF success rates by 10%, according to current data from an analysis of several clinical trials involving patients.

Other Developments at Embryonics

Embryonics continues to work on the implementation of artificial intelligence to improve reproductive technologies and offer more options to couples facing infertility issues. The combination of machine learning technologies and deep data analysis enables the creation of new diagnostics and increases the chances of successful treatments. In an environment where each step of the IVF procedure is important and impacts the final outcome, innovations like these can significantly change the approach to infertility treatment.

Monitoring and New Developments

The company intends to use its developments not only to select embryos but also to ensure better monitoring of their development at all stages, which will help improve their health and ultimately the success of implantation. The use of Ubar technology will help reduce the emotional and financial burden associated with failed IVF attempts and provide more accurate data to inform decisions on the way forward.

Conclusion

In summary, artificial intelligence and machine learning technologies such as Ubar are becoming an important part of the IVF process, enabling more accurate predictions, better quality selection, and consequently a greater likelihood of success. These developments represent a step forward in treating infertility, improving the lives of many couples seeking to start a family.