STAT+: In radiology, AI is blurring the line between technology development and clinical practice

STAT+ reports on how AI is blurring the boundary between technology development and clinical practice in radiology. The excerpt recalls that a decade ago machine learning scientist and Nobel laureate Geoffrey Hinton warned radiologists were like a coyote already over the edge of a cliff but not yet looking down, arguing deep learning was improving so quickly that people should stop training radiologists and predicting AI would outperform radiologists within five to ten years.

That timeframe has now elapsed, but radiology is not passively waiting to see how the technology reshapes the profession. A growing number of radiology practices, particularly outpatient and teleradiology groups, are aggressively embracing AI by developing and acquiring their own technology, deploying it in-house, and marketing "AI-native" capabilities to both radiologist employees and hospital customers.

The item is a STAT+ exclusive article. The accessible excerpt also notes the reporter's coverage focus on health technology's impact on patients, clinicians, and businesses, including the price tag of clinical AI, digital health at the FDA, and the boom in direct-to-consumer telehealth.