The advances in assisted reproductive sciences have been in manifolds, since the birth of Louise Brown, the first baby conceived through IVF in 1978. As the study tries to comprehend the process of natural reproduction and replicate it, more and more families are now able to bring their child into this world through it.
Continuous research and development is making reproductive technology more effectual, accessible, safer and affordable. It has blessed the childless couples with the joy of parenthood, making them bear ‘healthy’ babies (with better assurance than the process of natural birthing). However, talking about the future of assisted reproductive technologies, the practice is certainly gaining more momentum.
According to Dr Gautam Allahbadia, an IVF specialist in Mumbai, “Several approaches are currently being explored for significant improvements in success rate, which is expected to increase through a better understanding of embryo quality. Thus, resulting in quick identification of the right embryo for transfer.”
AI in concordance with Embryo Identification
With the integration of AI technology in the process of medical reproduction, the levels of precision, and accuracy have increased. Analysis of the data proved that Machine Learning Algorithms applied to large clinical data sets could predict the outcome of the IVF treatment with high accuracy. With the use of new imaging and sophisticated genetic tools, artificial intelligence is capable of highlighting the most viable embryos. They can identify the accuracy of a 5-day-old, In Vitro fertilized human embryo’s potential of turning into a successful pregnancy. The technique, which analyzes time-lapse images of the early-stage embryos, could improve the success rate of IVF and minimize the risk of multiple pregnancies.
“By introducing new technology into the field of IVF, we can automate and standardize a process that was dependent on subjective human judgment,” explains Dr Gautam Allahbadia, one of the top infertility doctors in Mumbai.
How are the chances of successful pregnancy being augmented through Deep Learning?
Through the modern-technological practice of deep learning, medical researchers can understand the intricate neural networks of the brain. When a computer is fed with new information, its ability to recognize the desired patterns improves automatically.
It can distinguish healthy embryos from unhealthy ones. However, it is critical to have an adequate source of data to provide the precision of outcomes. This computational approach has mitigated the chances of multiple pregnancies, miscarriages, premature delivery, through precisely addressing the maternal age and the quality of multiple embryos for achieving the best combination for a successful procreation.
AI systems for IVF are still in their nascent phase but have shown tremendous potential. However, consequential progress has been made on clinical and technical parameters to improve the algorithm, and further optimize embryo selection, and the rate of successful pregnancies.