Latest News
2022.06.14
AI embryo selection accuracy breaks through again, improving the success rate
A breakthrough in AI embryo selection could boost IVF success rate
In the past, IVF embryos with better quality were filtered out through PGS(PGT-A) of the third-generation IVF technology to increase pregnancy rate. It is found out that the failure rate is higher for women of advanced maternal age (age>35 years old) since they have fewer embryos that can be implanted after egg retrieval than that of ordinary people.
The main reason is that they do not have enough embryos to carry out PGT-A (PGS) which can detect chromosomal abnormalities. LWH’s AI embryo selection technology uses real-time embryo images and big data to predict embryos implantation potential.
One of the key factors affecting IVF success rate is the quality of embryo.The older women are more likely to have ova with low quality and quantity. They may suffer from lack of embryo or low chance to develop to blastocyst stage, and not suitable for biopsy to perform PGT-A.
AI embryo selection has breaks through the limitation of PGS
To compensate for PGT-A limitation, LWH combined the time-lapse system and AI deep learning module, and developed the ‘Artificial Intelligence Embryo Dynamic Image Analysis System’, provide a more standard and more precise embryo grading method.
LWH’s research breakthrough in AI embryo selection could boost IVF success rate
With more than 38 years of experience in field of reproductive medicine, LWH’s reproductive medical team is the earliest research team that invested in Artificial intelligence reproduction technology in Taiwan, 2017. LWH has also published research breakthroughs in AI embryo selection technology on ESHRE in 2019.
The reliability of the AI embryo selection system depends on its database and the experience accumulated by different experts on embryo morphology. Besides using the built-in database provided by the Time-lapse manufacturer, LWH has integrated the clinical research database into the embryo selection system. LWH has conducted more than 4,000 cycles of artificial reproductive treatment every year and accumulated successful experiences of more than 25,000 IVF treatments. With the huge database of IVF treatments and more than 38 years of reproductive medicine experience, LWH can provide more effective treatments for IVF patients in Taiwan.
Dr. Chun-I Lee and the Reproductive Medicine team of LWH have published a new breakthrough in AI embryo selection technology on the European Society for Reproductive Medicine (ESHRE) in 2021. The embryo images were imported into the AI deep learning module, and the decision tree was constructed based on 3 different embryos cultivation periods (time partitions) and 3 different algorithms. This system can be used to analyze the growth pattern of embryos and evaluate which candidate embryos with higher-potential for success implantation. The overall pregnancy rate has increased to more than 70%, and the abortion rate has also dropped significantly to 5 %. Experts from all over the world have expressed great interest in this research, which could be a benchmark for domestic AI embryo selection data.
Researches have demonstrated that AI embryo selection system may be a benefit for women with less embryos or have no blastocyst stage embryo. According to the continuous time-lapse monitoring in embryo development and AI computing analysis, AI embryo selection system can predict the implantation potential of embryo and used as an auxiliary assessment for IVF.
• Low ovarian reserve or poor ovarian function
• Poor response to ovulation-stimulating drugs
• Embryos cannot be cultured to the blastocyst stage
In the past, IVF embryos with better quality were filtered out through PGS(PGT-A) of the third-generation IVF technology to increase pregnancy rate. It is found out that the failure rate is higher for women of advanced maternal age (age>35 years old) since they have fewer embryos that can be implanted after egg retrieval than that of ordinary people.
The main reason is that they do not have enough embryos to carry out PGT-A (PGS) which can detect chromosomal abnormalities. LWH’s AI embryo selection technology uses real-time embryo images and big data to predict embryos implantation potential.
One of the key factors affecting IVF success rate is the quality of embryo.The older women are more likely to have ova with low quality and quantity. They may suffer from lack of embryo or low chance to develop to blastocyst stage, and not suitable for biopsy to perform PGT-A.
AI embryo selection has breaks through the limitation of PGS
To compensate for PGT-A limitation, LWH combined the time-lapse system and AI deep learning module, and developed the ‘Artificial Intelligence Embryo Dynamic Image Analysis System’, provide a more standard and more precise embryo grading method.
LWH’s research breakthrough in AI embryo selection could boost IVF success rate
With more than 38 years of experience in field of reproductive medicine, LWH’s reproductive medical team is the earliest research team that invested in Artificial intelligence reproduction technology in Taiwan, 2017. LWH has also published research breakthroughs in AI embryo selection technology on ESHRE in 2019.
The reliability of the AI embryo selection system depends on its database and the experience accumulated by different experts on embryo morphology. Besides using the built-in database provided by the Time-lapse manufacturer, LWH has integrated the clinical research database into the embryo selection system. LWH has conducted more than 4,000 cycles of artificial reproductive treatment every year and accumulated successful experiences of more than 25,000 IVF treatments. With the huge database of IVF treatments and more than 38 years of reproductive medicine experience, LWH can provide more effective treatments for IVF patients in Taiwan.
Dr. Chun-I Lee and the Reproductive Medicine team of LWH have published a new breakthrough in AI embryo selection technology on the European Society for Reproductive Medicine (ESHRE) in 2021. The embryo images were imported into the AI deep learning module, and the decision tree was constructed based on 3 different embryos cultivation periods (time partitions) and 3 different algorithms. This system can be used to analyze the growth pattern of embryos and evaluate which candidate embryos with higher-potential for success implantation. The overall pregnancy rate has increased to more than 70%, and the abortion rate has also dropped significantly to 5 %. Experts from all over the world have expressed great interest in this research, which could be a benchmark for domestic AI embryo selection data.
Researches have demonstrated that AI embryo selection system may be a benefit for women with less embryos or have no blastocyst stage embryo. According to the continuous time-lapse monitoring in embryo development and AI computing analysis, AI embryo selection system can predict the implantation potential of embryo and used as an auxiliary assessment for IVF.
Who is recommended to get AI embryo selection?
• Low ovarian reserve or poor ovarian function• Poor response to ovulation-stimulating drugs
• Embryos cannot be cultured to the blastocyst stage
| Preimplantation Genetic Testing for Aneuploidies (PGT-A) | AI embryo selection | |
| Technique | Embryos biopsy analysis | Time-lapse + AI algorithm |
| Cost | Charge by single embryo | Charge by whole batch of embryos |
| Limitation | • Unsuitable for low ovarian reserve • Unsuitable for embryos cannot be cultured to the blastocyst stage |
• Morphological assessment methods are limited • AI operations are affected by imported database images |
