Which are the opportunities that AI can bring to the field of Reproductive Medicine?

Time of publication: 1 year ago

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Which are the opportunities that AI can bring to the field of Reproductive Medicine?

The answer to this question can be twofold, as there are two conceptual levels on which AI can help in ART. On one hand, the opportunities address the needs of medicine in general and not only of assisted reproduction. These include standardization of processes and diagnostics, i.e., AI always returns the same quality answers independent of the time of day. It might sound surprising, but people do not act like that, e.g judges are more lenient after a good lunch. On the other hand, we believe that AI can improve the process of reproductive medicine, as it is very special. It is a well-controlled and reproducible process amenable to statistical analysis. 

We truly believe that by using AI we can break new ground in the fertility world. What we mean by that is setting new standards for fertility care, revolutionizing the way people experience the infertility journey and providing better access to fertility treatments worldwide.

Let’s just have a closer look at the numbers – every year demand for IVF procedures rises about five to ten percent! However, thanks to personalized recommendations based on AI, clinicians can choose the most relevant and least cost-consuming diagnostic and treatment paths. 

The Centers for Disease Control and Prevention reports that the success rate of IVF is increasing as the techniques are refined and doctors become more experienced. 

With AI technology, we can automate many time-consuming procedures and put the knowledge and experience of highly skilled healthcare professionals into every clinician’s hands, increasing patients’ chances for pregnancy. 

Staying with the numbers – every IVF cycle costs about 10 to 15 thousand USD. For patients, many cycles of treatment are financially and emotionally exhausting. Predictive systems built with AI algorithms, such as EMBRYOAID, can reduce the number of attempts by, for example, choosing an embryo with the best chance of developing into pregnancy. 

Our hope at MIM Solutions is that big data and machine learning, applied to the IVF decision process, can help make the treatment faster, cheaper and more successful.

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