A new model can detect abnormalities in x-rays better than radiologists—in some parts of the body, anyway.
The results: Stanford researchers trained a convolutional neural network on a data set of 40,895 images from 14,982 studies. The paper documents how the algorithm detected abnormalities (like fractures, or bone degeneration) better than radiologists in finger and wrist radiographs. However, radiologists were still better at spotting issues in elbows, forearms, hands, upper arms, and shoulders.
The background: Radiologists keep getting put up against AI, and they usually don’t fare even as well as this. Geoffrey Hinton, a prominent AI researcher, told the New Yorker that advances in AI mean that medical schools “should stop training radiologists now.”
Meta has built a massive new language AI—and it’s giving it away for free
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Yann LeCun has a bold new vision for the future of AI
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The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
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