How Artificial Intelligence Can Bring Smiles to the Faces of Infertile Parents

Medical practitioners are incorporating artificial intelligence (AI) via in vitro fertilisation (IVF) to improve the success rate of fertilization by predicting which embryo will result in a viable pregnancy.

Infertile females turn to IVF in the hope of improving their reproductive odds and get pregnant. But IVF is not always a success. As per a statistic, only 45% of IVF successes in the first transfer cycle, which increases to 65% after multiple cycles, in the USA. There are many reasons for IVF failures. For instance, the quality of embryos, age of eggs, the response from ovaries, and chromosomes are some of the reasons behind IVF failures. Amongst all the factors causing failures, the quality of embryos and the age of eggs are the most common reasons. Some of the embryos might have quality defects due to which they die instead of growing in the uterus. And, the quality of aged eggs worsens with time. AI is already transforming the healthcare industry in many ways. As another step in that direction now, by incorporating AI in IVF, medical researchers are trying to improve the success rate of IVF.

How AI in IVF Can Consolidate the Fertilization Process

IVF is a process where embryologists keep ten or more eggs in a lab for five days and then select the best candidates for fertilization. Embryo grading is a standard tool that they use to select embryos. But this system is subjective to many structural factors like symmetry, high cell number, and low fragmentation. But as mentioned earlier, the success ratio is very low. There have been instances where low-grade embryos have ended in pregnancies and perfect embryos not able to do it. But now AI can help increase the success ratio with its predicting capabilities. AI systems can be trained from historical IVF data. And then, with the help of ML algorithms, AI-enabled systems can determine what factors contributed most to the success or failure of the IVF process.

Also, AI-enabled IVF systems can perform a constant assessment of the growth of embryos during the five days of conservation to predict whether the embryo will stay alive or die after transplantation into the uterus. With the help of such predictions within the first five days, AI can help determine which embryo would develop a heartbeat. And since AI predictions help to make the IVF successful in the first cycle, it also speeds up the lengthy IVF process. 

IVF is a very costly process. According to an estimate, the average cost of a single IVF cycle is $12,000. This cost holds back many infertile parents from trying IVF. But, mainstream adoption of AI in IVF will eventually bring down the cost and raise the hopes of many infertile parents. Also, it will help improve the accuracy of predictions. According to a study, the current AI-enabled IVF systems can predict with 93% accuracy. But with mainstream adoption, AI systems will be able to self-learn from every embryo they analyze to improve the accuracy of prediction.