Photo credit should read ANNE-CHRISTINE POUJOULAT/AFP via Getty Images Google is developing artificial intelligence to help doctors identify breast cancer, according to a research paper published in Nature today. The model, which scans X-ray images known as mammograms, reduces the number of false negatives by 9.4 percent—a hopeful leap forward for a test that currently…
Google is developing artificial intelligence to help doctors identify breast cancer, according to a research paper published in Nature today. The model, which scans X-ray images known as mammograms, reduces the number of false negatives by 9.4 percent—a hopeful leap forward for a test that currently misses 20 percent of breast cancers, as reported byThe New York Times.
Today, breast cancer is the second leading cause of death in women, beat out only by lung cancer in its deadliness and overall prevalence. Early detection is the best defense most people have in identifying and treating the disease. Yet while mammograms are the most common detection tool, they miss a large number of cases. “Mammograms are very effective but there’s still a significant problem with false negatives and false positives,” Shravya Shetty, a researcher at Google who co-authored the paper, tellsThe Verge.
Ultimately, they were able to reduce false negatives by 9.4 percent and cut down false positives by 5.7 percent for women in the US. In the UK, where two radiologists typically double-check the results, the model cut down false negatives by 2.7 percent and reduced false positives by 1.2 percent. “The model performs better than an individual radiologist in both the UK and the US,” Christopher Kelly, a scientist at Google who co-authored the paper, tellsWired.
The system was not perfect. While researchers found that AI outperformed doctors in identifying breast cancer in most cases, there were also instances where doctors flagged cancer that the model originally missed. “Sometimes, all six U.S. readers caught a cancer that slipped past the AI, and vice versa,” Mozziyar Etemadi, a researcher at Northwestern University and another co-author of the paper, tellsThe Wall Street Journal.