As artificial intelligence evolves and the way physicians care for patients improves, ambulatory radiology technology will have recent impacts.
Already, artificial intelligence in ambulatory radiology is improving radiology screening by increasing detection capabilities and accuracy of basic diseases and cancers. Moreover, artificial intelligence in radiology helps with image analysis, improves the accuracy of MRI imaging, can improve patient care with faster results, reduces costs, and helps alleviate burnout among radiologists.
Future technological advances will continue to transform the medical imaging space, said Dr. John Simon, CEO of SimonMed Imaging. Simon will discuss artificial intelligence and radiological imaging at HIMSS25 in March in a session titled “The Future of Imaging: Artificial Intelligence in Ambulatory Radiology and MRI.”
Simon has been practicing radiology for over 30 years, specializing in women’s imaging, body imaging and interventional studies. At age 20, he graduated from Harvard in three years with Phi Beta Kappa and received summa cum laude honors. Simon completed medical school at the University of Chicago and accelerated radiology training and fellowship training at the University of Michigan.
We sat down with the doctor to discuss his HIMSS25 session to get a preview for readers.
Q. What exactly will you be doing during your session?
AND. The overarching theme of my session is the transformative potential of artificial intelligence in radiology, with a particular focus on outpatient imaging and MRI. In my session, I highlight the key benefits of AI in radiology, present case studies demonstrating AI in ambulatory imaging, and describe how AI is transforming healthcare as a disruptive and inventive tool.
My session will guide participants through the basics of artificial intelligence in radiology and enable them to understand key points that they can apply in their careers.
Today, technology is changing the shape of healthcare around the world, and radiology examinations are no exception. The integration of artificial intelligence in radiology has become a key topic for healthcare and IT professionals as healthcare professionals continually strive to understand and adapt to recent changes and advancements in the industry.
This session is especially relevant for those who want to actively learn advanced tools that can be incorporated into their own toolkit to boost diagnostic accuracy, improve patient outcomes, and streamline workflows. By coming to the session, HIMSS25 participants will gain a clear understanding of how artificial intelligence is driving change in healthcare.
Q. What is the focus of your session and what are some examples of AI in action?
AND. My keynote session will focus primarily on artificial intelligence models and their transformative applications in radiology. I will talk about case studies demonstrating the apply of artificial intelligence technologies such as cardiac artificial intelligence in preventive care, lung CT scans and artificial intelligence as a “second reading”, and bone scans with artificial intelligence to accelerate results.
My session covers each of these AI models as using AI as a reliable source that can be used in prevention tactics, using a second reading of MRI results, and using AI to accelerate results. By examining these case studies, audiences will gain a valuable understanding of how artificial intelligence is transforming radiology and driving broader advances in healthcare.
Q. What is just one of the various takeaways that you hope HIMSS25 attendees will leave your session with and be able to take advantage of when they return home to their organizations?
AND. The key takeaway I hope HIMSS25 attendees take away from my session is practical ways to incorporate AI into their healthcare practices, particularly in radiology, as well as provide reassurance and reassurance to those who are concerned about the apply of AI in care health.
Artificial intelligence is the most personalized and advanced technology available on the market today – using it for the first time can be intimidating and discouraging. After this session, I hope to teach my participants how to apply AI effectively and efficiently in their radiology practice without any doubts or concerns about the capabilities of AI.