top of page
Search

Doctors using AI catch breast cancer more often than either does alone

MIT Technology Review

July 11, 2022

Hana Kiros


Doctors using AI catch breast cancer more often than either does alone


Radiologists assisted by an AI screen for breast cancer more successfully than they do when they work alone, according to new research. That same AI also produces more accurate results in the hands of a radiologist than it does when operating solo.

The large-scale study, published this month in The Lancet Digital Health, is the first to directly compare an AI’s performance in breast cancer screening according to whether it’s used alone or to assist a human expert. The hope is that such AI systems could save lives by detecting cancers doctors miss, free up radiologists to see more patients, and ease the burden in places where there is a dire lack of specialists.


The software being tested comes from Vara, a startup based in Germany that also led the study. The company’s AI is already used in over a fourth of Germany’s breast cancer screening centers and was introduced earlier this year to a hospital in Mexico and another in Greece.

The Vara team, with help from radiologists at the Essen University Hospital in Germany and the Memorial Sloan Kettering Cancer Center in New York, tested two approaches. In the first, the AI works alone to analyze mammograms. In the other, the AI automatically distinguishes between scans it thinks look normal and those that raise a concern. It refers the latter to a radiologist, who would review them before seeing the AI’s assessment. Then the AI would issue a warning if it detected cancer when the doctor did not.


To train the neural network, Vara fed the AI data from over 367,000 mammograms—including radiologists’ notes, original assessments, and information on whether the patient ultimately had cancer—to learn how to place these scans into one of three buckets: “confident normal,” “not confident” (in which no prediction is given), and “confident cancer.” The conclusions from both approaches were then compared with the decisions real radiologists originally made on 82,851 mammograms sourced from screening centers that didn’t contribute scans used to train the AI.

The second approach—doctor and AI working together—was 3.6% better at detecting breast cancer than a doctor working alone, and raised fewer false alarms. It accomplished this while automatically setting aside scans it classified as confidently normal, which amounted to 63% of all mammograms. This intense streamlining could slash radiologists’ workloads. After breast cancer screenings, patients with a normal scan are sent on their way, whi