Nathan Blue, MD, thinks that artificial intelligence could make a crucial difference in delivering better answers—and better care—to people facing an increased risk of stillbirth.
He’s designing an AI-based tool that will scour massive databases of past pregnancy outcomes to find the hidden patterns of warning signs—from underlying genetic risk factors to environmental factors and clinical measurements—that mark the difference between a risky pregnancy and a relatively safe one.
The tool could then use those patterns to estimate the risk of stillbirth for future pregnancies. When a new patient arrives in the clinic with a fetus that is smaller than expected, their doctor could input their unique risk factors into the tool and it would calculate a personalized estimate of their risk of stillbirth.
Armed with that knowledge, a pregnant person and their doctor could make an informed decision about next steps: people with high-risk pregnancies could know to keep an extra close eye on their symptoms, and people at lower risk could have their worries relieved and not undergo unnecessary medical procedures.
“It could help people manage the stress and the burden of this experience, help reduce costs for people who don’t need tons of extra care, and prioritize who needs genetic testing,” Blue says.
