Individuals today prefer postponing the idea of starting a family until a later age, owing to their busy and demanding lifestyles. When they are eventually ready, they end up lamenting their infertility as a result of this. There is no denying the fact that ageing has a great impact on the fertility rate. In their 20s, both men and women have a high fertility rate, and as they get closer to their 30s, that rate starts to decline, which opens the gateway for complications. 


This is where modern fertility treatments such as in vitro fertilization (IVF) come into the picture. To help the sperm fertilize the egg and deposit the fertilized egg in the uterus, IVF employs a combination of medical treatments and surgical techniques. 


According to a MarketsandMarkets analysis, the global IVF market had a total value of $638 million in 2021 and is anticipated to increase at a rate of 9.1 percent to reach $987 million by 2026.


In fact, with the advent of modern technologies, the entire healthcare sector has undergone a drastic change. More precisely, the development of AI, in particular, has impacted several facets of healthcare provisions, ranging from data processing, diagnosis, and therapies, to tailored medications.


Benefits Of AI In IVF


Forty-eight million couples and 186 million people worldwide are infertile, according to WHO. This data hints that infertility has now become a major global health issue that is affecting millions of individuals. 


It is greatly influenced by a variety of environmental and lifestyle factors. For couples who are having difficulty conceiving naturally, IVF technology has shown to be extremely helpful in this situation. 


In addition, since AI entered the scene, it has become simpler for experts to navigate the complicated array of variables that are at play during the procedure and boost the success rate of the same.


There are several steps to the IVF process that combine both medical and surgical techniques, and AI can play a variety of roles in each stage. 


It can lessen the danger of multiple pregnancies and shorten the time it takes to get pregnant, in addition to assisting in analyzing the quality of sperm and eggs, predicting oocyte potential, and determining embryo viability. 


Furthermore, it helps in analyzing the uterus and determining the readiness and responsiveness of the endometrium, based on which it can estimate the implantation potential, which can then be used to decide the success of IVF.


The age and medical history of the patient are important considerations when planning an IVF cycle. Artificial intelligence can help reproductive specialists in this situation by enabling unbiased therapy decision-making. 


Additionally, AI algorithms help patients choose the best hormone replacement therapy in order to improve their chances of successful implantation.


Besides that, the selection of the embryo is another imperative step in the IVF procedure where AI is crucial. In the past, professionals used to visually assess an embryo's quality to determine whether it would produce a healthy pregnancy. Because each expert uses a different system to classify embryos, this consequently leaves room for subjectivity. 


However, with AI, professionals have a better chance of choosing the correct embryo because it automates the embryo selection process, increasing its accuracy by removing bias and reliance on subjective human judgment.


The AI-Enabled Future


There is no denying the fact that delaying parenthood is becoming increasingly popular among young couples. As a result, pressing concerns such as infertility arise. However, conceiving at a later age is now possible with the right treatment options, like IVF. 


Additionally, thanks to technological advancements like artificial intelligence, it is now simpler for fertility doctors to manage the wide range of variables that affect IVF treatment outcomes and improve its success rate. 


In reality, as technology develops, AI will give doctors a better understanding of the fertility treatment process by quickly evaluating patient data and empowering them to make better data-driven judgments.


(The author is an IVF and infertility specialist and a senior consultant at Apollo Fertility, Kolkata)


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