AI-powered tools in mammography screening deliver groundbreaking improvements in cancer detection, helping radiologists catch more cancers early while reducing unnecessary patient recalls. Study: Nationwide real-world implementation of AI for cancer detection in population-based mammography screening . Image Credit: Gorodenkoff / Shutterstock In a recent study published in the journal Nature Medicine , researchers examined the impact of artificial intelligence (AI) on cancer detection and recall rates.
Mammography screening contributes to reducing breast cancer-related mortality. Further, improving the sensitivity and specificity of screening could result in lower interval cancer rates, recall rates, and more effective treatment of breast cancer patients. Screening programs generate considerable volumes of mammograms, which, in most programs, require interpretation by two radiologists.
Additionally, a consensus conference may be required to achieve high specificity and sensitivity. As such, the work of radiologists involves repetitive tasks of interpreting a vast number of images weekly. Notably, this workload will likely increase as recent guidelines recommend mammography screening for additional age groups.
Incorporating AI into cancer screening programs could mitigate some problems. Studies suggest that AI is similar to and sometimes higher than radiologists in accuracy. Several studies observed increases in cancer detection for workflows integrating AI despite inconsisten.
