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Current and Emerging Insights on AI in Breast Imaging: An Interview with Mark Traill, MD, Part 2

Opinion
Video

In the second part of a three-part interview from the recent RSNA conference, Mark Traill, M.D., emphasizes patience and monitoring with the assessment of AI to ensure optimal use of the technology to help ease the strain of increasing breast imaging volume.

After using artificial intelligence (AI) clinically in tens of thousands of breast imaging cases for the past five years, Mark Traill, M.D., said benefits include “improved confidence, improved speed (and) improved accuracy.”

However, in an interview at the recent Radiological Society of North America (RSNA) conference, Dr. Traill cautioned that prudent assessment and evaluation of AI software is necessary to evaluate advantages and shortcomings of the technology.

“Now that isn't obtained within the first week of using an AI algorithm, which is something I like to point out. People looking at this technology will frequently ask for a trial, which is a great idea. … You need to spend time with (the technology). You need to know what (the) strengths and weaknesses are, which is something you can do with the internal validation. You can kind of see what it might not do so well. After you've been able to use it and be comfortable with it, then you can really push the gas pedal harder and see the advantages,” maintained Dr. Traill, a breast radiologist affiliated with the University of Michigan Health West in Wyoming, Mich.

(Editor’s note: For additional interviews from the RSNA conference, click here.)

Dr. Traill said radiologists should refrain from judgments about the AI software’s functionality for the first few months and emphasized ongoing monitoring of AI’s capabilities.

“Mammography is great for that. We are monitored all the time. They're keeping track of all our false positives and our callbacks through MQSA (Mammography Quality Standards Act). You need to do that for the AI too and that exercise, again, will make transparent more details about how the algorithm is working, and enable you to build trust sooner,” emphasizes Dr. Traill, an assistant clinical professor at the Michigan State University College of Osteopathic Medicine.

(Editor’s note: For related content, see “Current and Emerging Insights on AI in Breast Imaging: An Interview with Mark Traill, MD, Part 1,” “Diagnostic Imaging’s Top Five Mammography Content of 2024” and “Multicenter Study Identifies Key Factors Associated with Mammogram-Occult Ipsilateral Breast Cancer.”)

For more insights from Dr. Traill, watch the video below.

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