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Imagine getting an MRI of your knees and being told you have “mild intrasubstance degeneration of the posterior horn of the medial meniscus.”

Chances are, most of us who didn’t go to medical school are not going to be able to decipher that jargon as anything meaningful or understand what is actionable from that diagnosis. That’s why Stanford radiologists developed a large language model to help address patients’ medical concerns and questions about X-rays, CTs, MRIs, ultrasounds, PET scans, and angiograms.

Using this model, a patient getting a knee MRI could get a more useful and simple explanation: Your knee’s meniscus is a tissue in your knee that serves as a cushion, and, like a pillow, the meniscus has gone a little flat but still can function.

This LLM – dubbed “RadGPT” – can extract concepts from a radiologist’s report to then provide an explanation of that concept and suggest possible follow-up questions. The research was published this month in the Journal of the American College of Radiology.

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A study from Profound of OpenAI's ChatGPT, Google AI Overviews and Perplexity shows that while ChatGPT mostly sources its information from Wikipedia, Google AI Overviews and Perplexity mostly source their information from Reddit.

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