RSNA 2018: The AI Will Read Your Images Now

The Annual Meeting of the Radiological Society of North America (RSNA) was held in Chicago the week after Thanksgiving, and artificial intelligence (AI) was one of the dominant themes of the event. Despite a major snowstorm, over 50,000 attendees braved the weather to attend the conference.

Following the pattern of the past several years, new hardware introductions were few, with most of the major vendors renaming and reconfiguring systems and segmenting the modality offerings more broadly to address the concerns of price-sensitive buyers. The real headline of the week was the never-ending drumbeat around the use of artificial intelligence and machine learning in medical imaging. It seemed like every vendor exhibiting at RSNA 2018 had an AI offering or a product that was AI-aided, AI-empowered or whatever adjective you wish to use on the back end, as long as AI was on the front end. The airwaves were filled with data points and bold statements challenging reason with rhet­oric.

The AI frenzy appears to be triggering a rush to build anything with AI attached, including algorithms, apps and point solutions. Therein lies the problem. It is important to understand how the algorithms are constructed, what data sets were used to train the algorithms, and how the results from the test sets used to train the AI compare to real-world results.

The good news from all the AI hoopla at RSNA is that the radiology community has moved past the concerns expressed in past years about AI replacing radiologists. AI isn’t a replacement of human capabilities. It’s a reinvention of what it means to leverage the power of machines at scale, and a way to augment the most humanis­tic aspects of care.

The promise of AI is to complement the human interface, allowing doctors to be healers, not data entry clerks. And radiologists have decided to take control of the development of this important tool. RSNA announced a new journal to begin publication in 2019 devoted to AI in medical imaging. RSNA leadership has formed a steering committee to evaluate AI products developed for use in imaging and report on how well they perform.

With all the interest in AI, how do you determine which applications are right for your organization and separate the marketing hype from the clinical reality? Sg2 recommends asking specific questions to potential vendors, such as “Does your software have an accountability or auditing feature that allows me to see the rationalization of its decisions?” and “What are your sales to date, and who are your current customers?”

The promise of AI is not waning; indeed, it is brighter than ever. What we need to do moving forward is to become more purposeful, think more holistically and use AI to actually humanize health care.

Sg2 is here to help you optimize your technology resources to provide the high-quality, high-value care required for success in the future. Read the full Expert Insight for a more detailed list of questions to vendors, and contact your account team if you have questions or would like to have a more in-depth conversation on this or other technology topics.

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