With 10-15% of mammograms requiring additional diagnostic review, the two partners are counting on AI technology to help prioritize mammograms that require further review at a faster rate. The model was developed to identify mammograms with a higher probability of breast cancer and provide these patients with immediate medical attention, reducing diagnosis time and thereby providing better patient outcomes.
Building on research published in 2020 by Northwestern Medicine, Google Health, and the NHS that highlighted AI models that analyze de-identified screening mammograms, the Google-funded study will explore the possibilities arising from the results of this research.
In the study, participants will take a routine mammogram that will first be reviewed by the AI tool and then by a physician. The AI review will only take a few minutes, and the researchers emphasized that this extra step will not increase the amount of time patients have to wait for their mammograms to be reviewed.
The purpose of the study is to determine how the results provided by the AI tool can be used to help prioritize the order in which mammograms are reviewed by the physician. If the technology identifies that a mammogram shows areas that are more likely to have cancer, the radiologist can perform an immediate review of the mammogram, followed by a same-day test, at the physician’s discretion and if the schedule allows, to more accurately assess the presence of cancer.
The use of AI in the breast cancer diagnosis process is intended to speed up the process and this optimization of breast cancer diagnosis is expected to improve patient outcomes by detecting cancer earlier, which means it will be smaller and therefore more treatable, saving more lives.