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STAT+: AI-based mammography is here, and it has a trust problem
Radiologists interpret more than 40 million mammograms in the United States every year. In 2025, AI tools to help detect or diagnose possible cancer will be applied to millions of…
Radiologists interpret more than 40 million mammograms in the United States every year. In 2025, AI tools to help detect or diagnose possible cancer will be applied to millions of them.
As the Food and Drug Administration has cleared several AI algorithms to analyze mammograms, some imaging centers are adopting them en masse. RadNet, which owns more than 400 U.S. radiology practices, says it deploys its own AI algorithm in 600,000 mammograms every year. It recently acquired another company with an AI mammogram algorithm, iCAD, which claims 17% of U.S. radiology practices as customers. Another AI company, Lunit, says its tools were used in more than a million breast exams in the last year, and just inked a deal to integrate into more than 170 SimonMed outpatient imaging centers in the U.S.
Enthusiasm is growing for the technology, as prospective trials conducted in Europe suggest that some AI tools can detect more cancers than radiologists alone. But beyond radiology networks that are implementing their own algorithms, many imaging centers and the radiologists who work for them are still skeptical.
