Using artificial intelligence (AI) to help doctors read mammograms can reduce the scary phone calls or messages to patients requesting more testing, when nothing more may be needed.

It’s called AI-assisted breast cancer screenings, and the study was done at Washington University School of Medicine in St. Louis in collaboration with Whiterabbit.ai, a Silicon Valley-based technology startup.

According to a Washington University School of Medicine news release, the study shows how using artificial intelligence to supplement radiologists’ evaluations of mammograms may improve breast-cancer screening.

“At the end of the day, we believe in a world where the doctor is the superhero who finds cancer and helps patients navigate their journey ahead,” said co-author Jason Su, co-founder and chief technology officer at Whiterabbit.ai. “The way AI systems can help is by being in a supporting role. By accurately assessing the negatives, it can help remove the hay from the haystack so doctors can find the needle more easily.”

School of Medicine researchers say the algorithm they developed   identifies normal mammograms with very high sensitivity. They ran a simulation on patient data to see what would happen.

The simulation revealed that fewer people would have been called back for additional testing, and that the same number of cancer cases would have been detected.

So, the researchers conclude the AI may improve breast-cancer screening by reducing false positives without missing cases of cancer.

“False positives are when you call a patient back for additional testing, and it turns out to be benign,” explained senior author Richard L. Wahl, MD, a professor of radiology at Washington University’s Mallinckrodt Institute of Radiology (MIR) and a professor of radiation oncology. “That causes a lot of unnecessary anxiety for patients and consumes medical resources. This simulation study showed that very low-risk mammograms can be reliably identified by AI to reduce false positives and improve workflows.”