Rather than feeling threatened by AI in your radiology practice, embrace the technology as a tool that can provide additional clarification and act as an additional set of eyes. In an interview with Diagnostic Imaging, Randy Miles, M.D., MPH, and assistant professor of radiology at Harvard Medical School, commented that what [AI in mammography] boils down to is, “how we can improve workflow and efficiency and radiologist interpretative performance.”

1. AI in mammography helps clear patient backlogs

COVID-19 put a pause on many things in 2020, including routine mammograms and breast screenings of patients who felt more comfortable waiting or who did not think it was safe to go in for routine exams during the pandemic. As vaccines are more readily available and coronavirus numbers have gone down in many areas of the country, it means that many radiologists are feeling the pressures to keep up with a new demand for mammography screenings.

How AI is helping: By reducing reading time, in particular on benign cases, delivery of interpretations and diagnosis is faster and reporting turnaround time reduced.

2. AI reduces the need for additional patient callbacks

Patients don’t want to hear that they need to come back for additional screenings and you don’t want to have them come back if they truly don’t need to. In fact, nearly 10% of every screened woman is recalled for more tests (but less than 1% of them is typically diagnosed with cancer).

How AI is helping: By using artificial intelligence to assess more questionable scans, physicians have a second set of eyes to analyze findings and double-check benign or malignant masses which may cut down the amount of patient recalls needed each year.

3. AI picks up the slack in a time of radiologist shortage

There is currently a shortage of breast imaging specialists in the U.S. and that shortage is predicted to continue as we experience effects from the pandemic and other factors through the next decade. Thus, with a backlog of patients and smaller teams and personnel resources, radiologists are feeling burnout and the need to implement new technologies to aid in delivery of mammography screenings.

How AI is helping: An AI solution such as by MammoScreen® helps both in time spent reading cases categorized as low suspicion (scores from 1 to 4) which can represent up to 75% of your screening population. AI provides confidence and shaves off time in the process which adds up throughout the year.

4. AI promotes retention and talent development

While there may be a shortage of radiologists, there isn’t a shortage of radiology programs and there are several prestigious programs throughout the country trying to figure out how to integrate AI into their training. Residents and attendings are learning invaluable skills in AI and machine learning through universities like Duke, Stanford and Yale.

How AI is helping: Implementing a powerful AI system in your practice can help attract top talent and retain talent looking to work for companies that embrace technology and continued learning.

Transform your practice for continued success by implementing AI in mammography. We want to walk you through the process. Book a free, 10-minute demo today to learn how you can bring another set of eyes to your practice for efficiencies in screening and patient care.