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?
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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