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Where radiologists see the added value of machine learning—see the survey results

AI and machine learning are set to disrupt the practice of radiology. How and to what extent, we do not yet fully know. What does the ideal combination of radiologists and machine learning look like? Who is in the driver’s seat and when? Get your own copy of the new report>>

Using a case of prostate cancer as a clinical example, we asked radiologists in Scandinavia, Benelux, and the US for their perspectives on machine learning in radiology. What do radiologists think are the right tasks for machine learning applications? Where on a scale between supportive workflow-related tasks and making diagnostic decisions do radiologists see a value in machine learning applications? Can the results from machine learning algorithms be trusted?

* Get all the insights here

 
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