Sectra investigates:

The return on investment for AI in radiology

The use of artificial intelligence (AI) in radiology has been on the rise for several years. To find out what drives the return on investment (ROI) for implementing AI, Sectra interviewed six leading radiologists:

  • Prof. E. Naaktgeboren (Bravis Hospital, the Netherlands),
  • Dr. M. Kock (Albert Schweitzer Hospital, the Netherlands),
  • Prof. E. Ranschaert (Elisabeth-TweeSteden Hospital, the Netherlands),
  • Dr. M. Kruit (Leiden University Medical Center, the Netherlands),
  • Dr. T. Lindahl (Unilabs, Sweden), and
  • Dr. R. Malik (Royal Bolton Hospital, UK).

As pioneers in their field, they have participated in one or more pilot programs involving various AI applications, such as ChestEye, Transpara, contextflow, cNeuro, and qXR. In this article, they will share their experiences and insights on how the ROI varies between various AI applications and use cases.

Stop being told what AI can do. Start with the problem you want to solve, and then find a product that can potentially solve it.

Dr. Malik, Clinical Lead for Radiology, Royal Bolton Hospital, UK

As a pathologist or radiologist, there’s a limit to the number of cases you can report per day before sacrificing quality due to fatigue. Because it takes several years to train a radiologist, I don’t see how we can do without AI in the long run.

Dr. Lindahl, Medical Director, Unilabs, Sweden

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