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AI and Fertility: The Journey To Better Fertility Treatment

A Cutting-Edge Discussion about AI’s Eminent Role in Reproduction


Artificial intelligence has been widely useful in the diagnosis and treatment of diseases. However, little has been discovered about its capabilities in the realm of fertility treatment. Well, all that is about to change because we will soon experience the first application of AI in Assisted Reproductive Technology (ART). The topic was a highlight at the recently-concluded annual conference organized by the Progress Education Trust. Those involved in the discussion divulged how AI and fertility might impact the future of fertility-related healthcare.

The Role of AI in Fertility Treatment

Identifying Embryos and Gametes

“It was made clear that radio-frequency identification codes can assist in identifying embryos and gametes and thus automate their addition and removal.”

One main talking-point concerned how the use of AI-based tools and technology might assist in improving the success rate of ART by addressing some of the significant challenges presented during the process. It was made clear that radio-frequency identification codes can assist in identifying embryos and gametes and thus automate their addition and removal.

A One-Stop Mini-Lab

Another major hurdle ART presents is the prohibitive size of the laboratory and tools used. The discussants were confident that the integration of AI can be a stepping stone in the creation of a one-stop mini-lab capable of diminishing the need for large IVF laboratories, conventional incubators, and costly specialist equipment. That will save space and reduce expenses. 

Dr. Cristina Hickman, the chief scientific officer at Apricity, a virtual fertility clinic, explained that during a lapse culture, many images and data points are created as the embryo develops. She went on to say that such a large amount of information might inspire the creation of algorithm-based standard classification. This would assign a score to each embryo and thus predict its successful implantation potential.

All told, that process would save time and money while meaning more babies and safer practices.

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The Data Already Exists

How would AI and fertility become a reality? Where could we get this valuable data from? All the necessary information is already available throughout IVF labs and centers! Additionally, machine learning is more than equipped to account for population diversity and overcome conflicting pieces of evidence. 

As Dr. Hickman wrapped up her presentation, she emphasized that AI could improve all aspects of IVF treatment, before and after embryo selection. She also expressed confidence that patient data could be protected within the secure architecture offered by blockchain technology.

Cristina Hickman – Apricity Blockchain Talk May 2020

Australia Leading the Way?

Similar to what Dr. Hickman spoke about, Virtus Health Group, Australia’s leading fertility provider, has developed IVY.

IVY is an AI system that predicts the likelihood of a viable pregnancy for each prospective embryo for women undergoing IVF. This allows embryologists to assist in achieving successful pregnancies efficiently and quickly.

Recent newer incubators with time-lapse imaging have granted embryologists access to more possibilities in embryo selection. Still, none have successfully improved the process. Enter IVY, which utilizes a combination of AI and machine learning to predict whether or not an embryo can develop a fetal heart, which is a good indicator of a successful pregnancy. 

IVY conducts a three-dimensional assessment of embryo growth throughout all stages of development. Just like every other AI-based tool, IVY trains itself to single out those most promising by conducting an objective analysis of the images with no pre-determined parameters. Eventually, IVY assigns an “embryo score” to each embryo. The higher the score, the better the chances of producing a healthy baby.

Not So Fast!

Wang et al. (2019), in their report, identify that while image analysis of sperm cells and embryos and the prediction of ART outcomes can possibly assist fertility treatment, far more investigation is required. The researchers also caution that machine learning models can lack a universal understanding of inner workings, thus leading to possible ethical and legal risks. 


The utilization of artificial intelligence in fertility treatment can reduce costs and improve success rates. AI-based systems like IVY can play a significant role in making embryologists’ work easier and more effective via data-driven, accurately selected embryos.

Please note that IVY is an early attempt at implementing AI in the field. Researchers are yet to thoroughly test its clinical application, but with time this research could lead to long-awaited breakthroughs in fertility treatment.

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