AI Adoption Trends in Medical Imaging

We hope you find this article interesting and informative. We used our Reaction research platform to gather all of the data for it. Whether you’re a hospital, clinic, payer, or vendor, you too can use our platform for your own research programs and projects.

AI continues to be a hot topic in healthcare, specifically as it relates to medical imaging. We’ve been researching AI adoption trends for the past 3 years and wanted to get a quick pulse from radiology and medical imaging professionals to see what’s changed. This time we specifically wanted to see what kind of value or ROI their departments are realizing from adopting AI and to see why some organizations haven’t yet taken the plunge.

Importance of AI

AI continues to rise in importance. When we first started doing this research in 2017, only 65% or organizations felt that AI was important compared to 83% today. If a participant said that AI was important we then asked that person to justify, explain if you will, why they feel it is important. The answer were diverse – quality, productivity, detection accuracy, and the like

“it will assist with better patient care and outcomes. It should increase the accuracy of findings with Imaging procedures and help in obtaining a correct diagnosis.”

"...I strongly believe it will drastically change the future of radiology, the new radiologist will have a job more focus on specific or complex analysis of cases rather than detection which remains still today a large volume of the work we do... No one should fight that change which is welcome for a better care I think. We just need to adapt and adjust.”

Where AI Is Being Used

Over the past 3 years algorithms focused on lung scans and on breast imaging have been the most prevalent and that continues to be the case. The difference is in the delta between these two areas. This year breast imaging algorithms are being used far more than are those for studies focused on the lungs while in previous years the usage delta has been much smaller.

"Cost of adopting new AI tech will be key. If the investment cost can be easily recouped with uptick in efficiency and throughput then more people will adopt it. Also, will have to be easy/user friendly as many older physicians struggle with new technology."

AI Vendors

Given that breast imaging is the top clinical use case area, by far, it’s not too surprising that iCAD and Hologic are the top vendors mentioned as supplying AI algorithms to hospitals. It will be interesting to see if the standalone VC-backed AI players can make further inroads.

“It is difficult to judge the competitive landscape. There are many companies that offer similar AI products and it is hard to determine which one to invest in for a particular clinical application. It also seems unlikely that many of the AI specific companies will survive long-term in this competitive environment.”

Simply put, AI is the present and the future. It’s a proven technological advancement that has emerged in every industry and has quickly made its way into healthcare (specifically medical imaging). More and more algorithms are developed every month with increased applicability and efficacy. After years of doing research on this topic, it’s become obvious that AI is not going to replace radiologists (or almost any other clinician for that matter) but what it will do is help these clinicians perform, many of their critical job functions, better.

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