Generative AI, particularly large language models, is becoming significant in radiology, enabling practitioners to streamline non-clinical tasks that demand less clinical knowledge. Contrary to earlier predictions of AI replacing them, radiologists are leveraging such technologies to alleviate workforce challenges. Over 1,000 FDA-approved AI/ML medical devices exist, primarily for radiology, with many stemming from traditional machine learning rather than generative AI. As AI transforms workflows, the industry is seeing a surge in AI-focused companies, making radiology a notable case of AI's potential in healthcare.
"Rather than being worried about AI, radiologists are hoping AI can help with workforce challenges," explained Dr. Curt Langlotz, the senior associate vice provost for research and professor of radiology at Stanford.
Hinton's notion wasn't entirely off-base. Many radiologists now have access to predictive AI models that classify images or highlight potential abnormalities.
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