During a night shift when she was a resident at Yale New Haven Hospital, Cristiana Baloescu was taking care of a patient with a complex presentation of symptoms. The patient was experiencing some back and leg pain. But they also looked really sick.
"Emergency physicians spend years developing the skill to recognize whether a patient looks sick or not," said Baloescu, now assistant professor of emergency medicine at Yale School of Medicine. "With patients who look sick, we spend a lot of time thinking what's going on because if they're doing well now, they probably won't be doing very well in the next hour or two."
Luckily, Baloescu figured out what was going on with the patient pretty quickly. Using what is known as a point-of-care ultrasound, she discovered that the patient had an aortic dissection, or a tear in the aorta - the body's main artery that carries blood from the heart to the rest of the body.
"I saw what I needed to see with ultrasound, and we were able to get that patient the immediate medical care that they needed, and thankfully, the patient lived," she said.
Point-of-care ultrasound is an ultrasound doctors perform and read at the bedside, giving fast, clear answers to guide care, unlike traditional scans that require a specialist and are more detailed. Portable ultrasound machines provide detailed images to physicians like Baloescu in real time so they can make informed decisions quickly.
These days, artificial intelligence (AI)-guided ultrasounds could make care even more responsive to patients' needs while also supporting clinicians in making faster, more confident decisions. At Yale, Baloescu has been studying the use of AI-guided ultrasounds, specifically lung ultrasound imaging, which is essential for identifying conditions such as pneumonia and pulmonary edema.
In an interview, Baloescu discusses her interest in point-of-care ultrasound, what AI could mean for this technology, and how that could improve patient care.
The interview has been edited for length and clarity.
