A decade ago, machine learning scientist and Nobel laureate Geoffrey Hinton made a proclamation that still puts radiologists on edge.<\/p>\n
\u201cIf you work as a radiologist,\u201d the so-called godfather of artificial intelligence said at a conference, \u201cyou\u2019re like a coyote that\u2019s already over the edge of the cliff, but hasn\u2019t yet looked down.\u201d Deep learning was getting so good, so fast, said Hinton, that \u201cpeople should stop training radiologists now.\u201d In five years \u2014 ten, max \u2014 AI would do better than radiologists, he predicted.\u00a0<\/p>\n
The clock has run out on that prediction. But the field of radiology isn\u2019t just staring at its shoes, waiting to see how technology upends the profession. Instead, a growing number of radiology practices, in particular outpatient and teleradiology groups, are aggressively embracing AI: developing and acquiring their own tech, deploying it in-house, and marketing their \u201cAI-native\u201d capabilities to radiologist employees and hospital customers alike.\u00a0<\/p>\n
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