The findings, derived from ACR's National Mammography Database, offer important clues as leaders seek to improve biopsy rates after screenings. 

This approach can be replicated by radiologist-led teams elsewhere, providing a "high-value, scalable opportunity" to reduce cancer screening disparities. 

Automatically scheduling patients for breast imaging also created a heavier administrative burden, researchers detailed Monday in JAMA Internal Medicine. 

According to one radiologist, the continued success of AI could make second reads for screening mammograms a thing of the past. 

Physicians at Northern Arizona Radiology reportedly had been forced to work long hours to re-read exams looking for missed cancers. 

“It’s vital that imaging centers have a process in place to provide ongoing monitoring of AI once it becomes part of clinical practice,” one expert noted. 

The largest diagnosis deficits were observed for breast, colon and lung cancer, experts detailed in JAMA Network Open. 

“The results suggest that mammography screening can be effective in older women, particularly as life expectancy increases,” researchers contend.