AI has a booming interest in the area of maternal and fetal medicine. Even though previous inventions in this delicate aspect of healthcare banked on an expert rule-based system to predict the risk of pre-term births in pregnant women, it is now up for more exciting AI advances. 

Maternal and Fetal Medicine is an area of medicine that focuses on the management of all health conditions affecting expectant mothers and their unborn babies before, during, and shortly after pregnancy. Under normal circumstances, pregnancies should progress without issues. Yet, due to unknown reasons, some pregnant women experience complications ranging from mild to severe, which can affect either the mother’s health, the baby’s health, or both. 

According to Johns Hopkins Medicine, some of the common complications experienced by women during pregnancy are high blood pressure, extreme morning sickness, gestational diabetes, and placenta previa – a condition where the baby’s placenta covers the mother’s uterus causing severe bleeding. Pregnancy complications are one of the leading causes of maternal mortality all over the world. This makes managing pregnancy and delivery for women living with chronic conditions before pregnancy more intricate. 

Maternal and fetal medicine is supervised by Maternal and Fetal Medicine (MFM) Specialists who work hand-in-hand with a medical team to ensure that both mother and child enjoy a smooth and safe transition through conception and delivery. Although they cater to all health categories of pregnant women, however, women with high risks are of special interest to them because they need more care. MFM specialists take note of any present ailment, medications, and impending complications to work out the most suitable treatment plan for both mother and child-in-utero. By leveraging on the power of AI and clinical data from Electronic Medical Record, complications are detected early for possible medical interventions to realize better outcomes for both. Here’s AI’s impact in the various areas of maternal and fetal medicine.

AI-assisted fertility

AI in maternal-fetal medicine isn’t restricted to pregnant women alone; it is also involved in helping women conceive. For women who struggle to give birth, calculating menstrual cycles, monitoring hormone levels, and lifestyle changes can be draining. Now many women have turned to AI to do the work for them. AI-assisted consumer apps like Flo use data on physical symptoms, menstrual cycle, and sexual activity to polish predictions on ovulation and fertility. This is enabled by its neural networks of 442 input units. Women get actionable tips and first-hand info on what they can do better to increase their likelihood of pregnancy. To date, it remains the number one period tracker in the U.S. and falls within the top ten worldwide.  

Likewise, some women need a form of assisted reproductive technology (ART) known as In-Vitro-Fertilization to give birth. A cycle of IVF costing an average of $12,000 excluding additional costs and a success rate of 20 – 35 % per cycle and odds of success increasing at multiple cycles, yet, most IVF procedures fail due to a faulty embryo selection method. 

One good news is that AI is finally here to make the process better. By training AI algorithms with thousands of embryo images of different quality, the algorithms select high-quality embryos with an accuracy of 97% than most embryologists. AIVF, an Isreal based reproductive innovation firm, utilizes the power of AI to streamline the process of IVF, making it faster, more efficient, and affordable. According to Daniella Gilboa, the Co-founder and CEO of AIVF, “AIVF plays a central role connecting the capabilities of deep learning and computer vision with clinical fertility care.”  Such an automated IVF framework is setting the pace for new trends in the fertility industry. 

“The revolutionary AI platform will transform the world of IVF by enabling better understanding and use of the vast amounts of data accumulating in the new digital age of embryology,” Gilboa concluded. With AI at the forefront of fertility procedures, infertility will be a thing of the past.

AI-powered ultrasound

An ultrasound exam is first carried out in the first trimester of pregnancy to check the fetal heart-beat and brain for any abnormal growth. It informs parents of the health of the growing fetus. It also helps to monitor the conditions of the internal environment and predict the due date. But ultrasound isn’t 100 percent precise because some abnormalities are not easily spotted in an ultrasound examination. Hence, some babies with congenital disabilities may look the same as ordinary babies. Besides, it requires the expertise of a sonographer to operate and technician error may interfere with results.

But by using computer vision which outstrips humans in spotting defects, artificial intelligence prevents this gamut of challenges. It spots, separates, and color codes scan images in an efficient peer-review process to check that they align with the normal anatomy of a developing fetus. This is a viable lender of last resort in speeding up the ultrasound process in busy clinical settings regardless of the sonographer’s expertise. 

The Butterfly iQ is a perfect example of such a device. As the world’s only AI-powered hand-held ultrasound, it has a high potential to detect and diagnose pathologies at the various phases of the ultrasound imaging workflow. It can also fast-track fetal surveillance in its entirety. This is foolproof of how AI is making medical devices and technologies for maternal and fetal medicine accessible, affordable, and more efficient. 

AI-assisted child delivery

AI isn’t resting on its oars any time soon. It is moving in leaps and bounds as it makes certain that every aspect of the mother and child care is reinforced. Over a year ago, the topic of AI-powered robots taking human births generated lots of debate online. Because nothing compares to the emotional support women get from the medical team at the point of delivery, there are concerns that these robots may be lacking in providing emotional care.

However, some MIT researchers have found an altruistic way to utilize robots for point of delivery care by inventing an AI robot that can assist with the medical scheduling of women in the labor room. When comparing accuracy levels with professional doctors and nurses, they found out that these AI robots had an accuracy of 90%. 

This led them to recommend AI as safe and perfectly suited for childbirth. In reality, future robots will take up auxiliary roles under the supervision of the medical team thereby, contributing to a holistic experience for both mother and child during the child delivery process. This will make a positive lasting impression beyond the moment of delivery. Just with every other area that AI has invaded, other than setting the pace for a new archetype, integrating AI algorithms in the backend of maternal and fetal care is a world of new possibilities we can’t wait to harness fully.  

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