Breast cancer is a disease that affects too many women around the world. More than 55,000 people in the UK are diagnosed with breast cancer each year and around 1 in 8 in the US.
Digital mammography, or X-ray imaging of the breast, is the most common method of cancer detection, with more than 42 million tests performed each year, in the US and UK combined. But despite the widespread use of digital mammography, early detection and diagnosis of breast cancer remains a challenge.
Reading these X-ray images is a difficult task, even for experts, and can often result in false positives and false negatives. In turn, these inefficiencies can lead to delays in diagnosis and treatment, unnecessary stress for patients, and increased workload for radiologists who are already in short supply.
Over the years, various studies have been conducted to find new techniques that make them more effective. Both the diagnosis and some findings published in Nature show that the AI ​​model of breast cancer detected in de-identified screening mammograms (where identifiable information has been removed) is more accurate, with fewer false positives and fewer false negatives; laying the foundations for future applications where the model could help radiologists to test breast cancer screening.
In collaboration with DeepMind, Cancer Research UK Imperial Centre, Northwestern University and the Royal Surrey County Hospital, the model was run to see if artificial intelligence could help radiologists detect breast cancer symptoms more accurately.
In making decisions, the model was less informed than human experts, who, as usual, accessed patient records and previous mammograms, while the model only processed the most recent anonymous mammogram, without additional information. Although working only with these X-ray images, the model of the individual outermost experts in breast cancer accurately identified.
Looking to future applications, there are some promising signs that the model has the potential to increase the accuracy and effectiveness of screening programs, as well as reduce waiting times and stress for patients.
The innovation of artificial intelligence includes the latest line in the detection and diagnosis of breast cancer, not only in the field of radiology, but also in pathology.
Thus, the inclusion of technology and digital elements in clinical practice, diagnosis and in the promotion of our services always makes a difference to health.
Source:
Shetty, MSS (2020, January 1). Using AI to improve breast cancer screening. Google.
