Interesting development. Researchers (one of whom has had breast cancer) have developed AI that can read mammograms in greater detail than the human eye. This would not do away with mammograms, but could lead to more wise and strategic use.
Here are a few snippets to give you the idea, but they are by no means, the whole picture. This is a 2,800-word story. I used the share link, so it should not be paywalled.
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As she and her team laid out in an article in the Journal of Clinical Oncology last month and explore further in an upcoming piece set to be published in Nature Medicine, by analyzing a mammogram’s set of byzantine pixels and then cross-referencing them with thousands of older mammograms, the AI — known as Mirai — can predict nearly half of all incidences of breast cancer up to five years before they happen.
…The mammogram is a little bit like Winston Churchill’s democracy: It’s the worst screening method, except for all the others. The approach — which uses low-grade radiation to examine breast tissue from multiple viewing angles — has become the gold standard over the past several decades, and many medical professionals swear by it as an uncomfortable but important safeguard. It also has drawn its share of critics in the oncology and women’s health communities who say it has led to unnecessary radiation exposure, overtesting, false positives and all the stress that comes with them.
…Many radiologists in the field are enthusiastic too. Katerina Dodelzon, Katzen’s colleague at Weill Cornell, noted the technology’s ability to take radiology “from diagnostic to prognostic” functions.
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There is, of course, resistance in the medical community…
The same optimism may not yet have taken hold with breast cancer surgeons or oncologists, who most directly advise patients on breast cancer risk. Requests for comment to such doctors at four high-level hospitals were declined, and one hospital staffer described an ambivalence among that group. Mathematical models are common in cancer treatments such as chemotherapy dosages, but that is more familiar to physicians than outsourcing a prognosis to a computer.
Even some radiologists are conflicted, fearing automation could take their jobs.
…While emphasizing that these technologies are meant merely as a tool for the human reader, Tobias Rijken, chief technological officer and co-founder of Kheiron Medical, also pointed to a machine’s comparative advantage in the life-or-death effort of breast cancer imaging. “An AI works 24/7, it doesn’t get tired, and it doesn’t have personal problems at home,” he said.
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