Artificial Intelligence in Radiology

There is a lot of hype around Artificial Intelligence (AI) in medical imaging recently. In the radiology community, there is concern over what the technology will mean for the future of the industry.

Last year, Toronto University professor and AI pioneer Geoffrey Hinton warned, AI will likely read medical imaging better than radiologists, resulting in unemployment across the industry, and that medical schools should stop training radiologists.1 Earlier this year, Vinod Koshla, a US venture capitalist and co-founder of Sun Microsystems stated in an interview that, “…the role of the radiologist will be obsolete in five years.”2 Unfortunately, this did not take into account the fact that being a radiologist goes way beyond the interpretation of images. AI is unlikely to replace radiologists anytime soon, rather it will increase the value they provide.

Increasingly, AI will be used in reading workflows and the interpretation of radiology images, to address the following challenges:

  • Demand: In most countries, there are not enough radiologists to meet the demand for diagnostic imaging services—radiologists are operating at, or near capacity. The situation will get worse as the demand for diagnostic imaging services grows, populations age and chronic diseases grow at a faster rate than new radiologists enter the domain.3 4 Radiologists have to deal with data overflow as radiology exams become more and more complex and the number of images per study grows. This has led to medical image interpretation becoming a bottleneck in healthcare today. Digital technology has helped to speed the imaging process, but this…

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