Ask a Scientist: How are researchers using AI to help pregnant women access ultrasounds?

Ultrasounds give women crucial information during pregnancy — they allow expecting parents to hear a heartbeat, count fingers and toes, check how many babies there are, see how they’re positioned, and so much more. But not every pregnancy gets this level of care. About two-thirds of people across the globe lack ready access to diagnostic imaging services, like ultrasounds and X-rays. And there aren’t enough sonographers to perform ultrasounds for everyone who needs them. So what do you do if you can’t get an ultrasound where you live?

Google researchers explored an AI tool for this problem through a research study with Northwestern and Jacarand Health. The research involved training healthcare workers to perform simple “blind sweep” ultrasounds and used machine learning models to interpret the results. With this approach, they were able to detect important prenatal information, like gestational age and fetal presentation, as accurately as a trained sonographer, giving women in under-resourced areas better information about what to expect ahead of one of the most significant events of their lives.

We sat down with Googlers Angelica Willis and Dr. Nichole Young-Lin to learn more about this research — and what it could mean for the potential future of ultrasound access worldwide.

What do you do at Google?

Angelica: I’m a software engineer and AI researcher. I’ve always been passionate about using AI for social good and healthcare equity. When we look at maternal care, technical advancements are only as valuable as the lives they impact. My motivation is building technology that actually reaches the people who need it most. And right now, my focus is making healthcare more accessible worldwide.

Nichole: I’m the in-house obstetrician-gynecologist (OB/GYN) at Google. I actually got my start in public health researching postpartum hemorrhage to reduce maternal mortality. That inspired me to become a doctor, but I soon realized that to address global inequities in medical access, we need the scale that technology can offer. I now work on a range of women’s health and consumer health projects at Google,a week while continuing to care for patients.

Why are ultrasounds so important?

Nichole: As an OB/GYN, we turn to ultrasounds for all sorts of questions. Is the baby growing appropriately? Are there anomalies? And we rely on early ultrasounds, in particular, to estimate gestational age: How far along is the pregnancy, and when is the baby due? Screenings, treatment, management, and being able to prepare for a safe delivery — that all depends on a timeline determined by gestational age.

Many people have irregular periods or don’t track their periods, so we can’t always rely on period history to estimate gestational age. And there can be serious ramifications for getting it wrong. Let’s say someone needs to deliver early because of a complication. You think you’re delivering a 37-week baby, but maybe you’re actually delivering a 34-week baby with less mature lungs. Those babies need very different levels of care when they’re born. When we’re able to accurately define the baby’s gestational age, we’re much better prepared to provide both the baby and the mother with the support they need after birth.

What’s keeping people from getting ultrasounds during pregnancy?

Nichole: Traditional ultrasound machines are bulky and expensive, creating a barrier to access. When they break in remote clinics, there’s often no one to fix them, and they require stable electricity when they do work. With recent developments in handheld ultrasound devices, we’ve seen greater potential for us to get ultrasounds to more women, especially in low-resource settings. The handheld machines are smaller and cheaper, and many are battery-powered, so they’re portable and easily accessible

Angelica: But even with advancements in portable device technology, it still takes two years of intense hands-on training to become a sonographer, resulting in a global shortage of sonographers who can perform prenatal ultrasounds.

Tell me about your research. What are you doing differently to solve those problems?

Angelica: We partnered with Jacaranda Health and Northwestern Medicine in our study of 1,000 mothers in Nairobi, Kenya, and 1,000 more in Chicago. We found our machine learning model could detect gestational age and fetal presentation as accurately as a trained sonographer.

In a traditional ultrasound, the sonographer has to move the probe around precisely to get specific measurements. And it’s really hard to get right. Our research involved a “blind sweep” ultrasound instead. Operators sweep the probe over the abdomen in a predefined pattern. And healthcare workers who’ve never performed an ultrasound before can learn how to do it in eight hours.

These blind sweep operators gather videos that help us get the imaging we need of the baby, and we built an AI model to analyze those videos. It can tell the operator if they need to redo the sweep. And it can estimate gestational age and indicate fetal presentation — what position the baby’s in. Crucially, all of that processing happens on the device, so it doesn’t require an electricity supply or even Wi-Fi to be able to provide the operator and the mother with the insights they need to prepare for birth.

What could this mean for maternal healthcare worldwide?

Angelica: We saw this project as an opportunity to demonstrate what’s possible in maternal healthcare. The research proves we can broaden access to expert-level care and put it directly into the hands of frontline community health workers.

Nichole: The goal of our research is to show how expanded access to life-saving ultrasound care could impact communities, and we’re getting there one step at a time. Through this research, we’ve made huge strides toward showing that this is a viable application of AI in maternal healthcare because we can use it across different patient populations and healthcare settings. But why stop at gestational age and fetal presentation — or even maternal healthcare? Ultrasound can be used for so many things, like seeing how much someone is bleeding after an accident or an injury. There’s so much potential for AI to help improve maternal health and healthcare across the board.