What radiology can learn from self-driving vehicles

AI is here. It’s in our apps, our home voice assistants, our transportation systems and much more. The adoption of AI technologies has increased dramatically in the past few years, with autonomous vehicles leading the way for many other industries to follow suit. In fact, the adoption of AI to enhance vehicles has created a framework that offers many lessons for other industries, medical included.

Radiology can approach the adoption of AI through the lens of the step-by-step structure of AI adoption in the auto industry. These five levels of automation are commonly referred to in the auto industry and can easily be applied to the levels of adoption that the field of radiology will face in the coming years as well. The framework serves as a model that can help us understand what to expect in terms of AI adoption in radiology, and when major shifts will take place.

I would like to invite you to read my full article, in which I have written extensively on this topic for the well-known publication, Radiology Today magazine.

Click here to read the full article and learn more about what radiology can learn from the step-by-step adoption of AI in the auto industry.

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