RSNA 2022: AI Highlights

The mission of RSNA, the Radiological Society of North America, is to promote excellence in patient care and healthcare delivery through education, research, and technological innovation. All of these were on display at the 2022 RSNA annual meeting, bringing together radiology professionals and industry partners to network, collaborate, and explore the latest advancements in the field of radiology.

The windy city, Chicago, Illinois, played host to the program, drawing radiologists from around the globe. A highlight of the RSNA annual meeting is the AI Showcase, a place to collaborate and explore current and emerging innovations in medical imaging. The Ferrum Health team was on the ground at RSNA, taking customers on an AI Partner Tour and hosting an AI roundtable discussion with radiology experts. The week’s Domain Knowledge shares AI highlights from RSNA 2022.

Ahead of RSNA, Charles W. Kahn, Jr, MD spoke with Radiology Business about ways AI is being used by radiologist and how that may evolve in the years ahead. You can follow the discussion via the video, An updated look at the use of AI in radiology.

What is the current state of radiology AI in radiology? Dr. Peter Chang of the University of California, Irvine shared his perspective in a video interview at RSNA 2022. This discussion focused on AI implementation trends.

The implementation of AI was a hot topic. Understanding the challenges of implementing AI in radiology can help health systems and radiology groups decide the best approach for their AI endeavor and set strategic priorities. But what are the issues that need careful thought and planning to avoid technical and organizational missteps? How to avoid the AI integration traps speaks to these concerns and shares experience from radiologists at the Mayo Clinic.  

The practical application of imaging AI was reviewed in various therapeutic areas, explored for the different benefits it can provide and focused on partnerships that can bring structure to the broader use of AI across radiology practices. Here are a few highlights from the week.

A recent study proved that using an AI system to send scheduling reminders to patients needing imaging follow-up significantly reduces patient no shows and potentially improves patient care and outcomes.

A deep-learning model that predicts the 10-year risk of death from heart attack or stroke by using a single chest x-ray was presented during RSNA.

Strategic Radiology is partnering with Ferrum Health to implement their privately deployed enterprise AI platform across all its member practices to discover, validate, and manage their AI algorithms.

AI can help radiologists detect more cancers and be used in consensus decision-making compared with radiologists alone. This team found a 27% increase in cancer detection rates using AI.

In double-reading scenarios, artificial intelligence (AI) can safely reduce breast imaging workload by over one-third by replacing one reader. In this study the researchers found they could have a substantial workload reduction of 33.8% and no missed cancers.

That’s a wrap for this week’s review of news and happenings in the healthcare AI space. In closing, I’ll leave you with an invitation to learn more about the benefits of using an AI Hub to manage multiple applications across your clinical needs and offer you personal demo of Ferrum’s platform and growing AI catalog.

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Kathleen Poulos

Kathleen is a registered nurse with a digital marketing background, a love for using technology to solve healthcare challenges and a passion for improving patient care.

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