The AI Assistant blog offers valuable information and perspectives from radiologists, patients, data scientists, and other stakeholders about artificial intelligence in medical imaging.

Tackling the Economics of Artificial Intelligence

To move AI algorithms into routine clinical practice, we’ll need fair compensation for their development. Figuring out how that will happen isn’t as simple as it seems.
By Bibb Allen, Jr. | Chief Medical Officer, ACR Data Science Institute | Apr. 19, 2018
Tackling the Economics of Artificial Intelligence

A key ingredient in moving Artificial Intelligence (AI) algorithms into routine clinical practice will be ensuring our healthcare system supports fair compensation for their development. However, figuring out how that will happen may not be as simple as it might seem.

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The Brave New World of Centaur Radiologists

With the so-called centaur approach, a hybrid of radiologist plus machine will define the next phase of radiology.
By Stephen M. Humphries, PhD and Raym Geis, MD | Apr. 12, 2018
The Brave New World of Centaur Radiologists

Computers are now very good at extracting meaningful information from pixel data in images. Applications of AI, such as automatic detection and recognition of faces in photos, have already become familiar in consumer products. The use of AI in medicine is taking off, and medical imaging is one of the fastest-growing application areas.

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Artificial Intelligence is Everywhere

AI has crept into all aspects of our lives, and the same will be true for radiology.
By Andy DeLaO | Patient Advocate | Mar. 20, 2018
Artificial Intelligence is Everywhere

I feel a vibration on my wrist that gently wakes me from my sleep. I roll over, touch the device on my wrist, and lay there for about five more minutes. Then I feel another vibration. I check the time on my phone. It’s 5:30 — time to get up.

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ACR Data Science Institute Update: What’s Ahead in 2018

The most important activity of the ACR DSI in 2018 will be the development of detailed AI use cases for the radiological sciences.
By Bibb Allen, Jr. | Chief Medical Officer, ACR Data Science Institute | Feb. 8, 2018
What is ahead in 2018

As we begin the new year, the ACR Data Science Institute (DSI) is celebrating its nine-month anniversary. While it might seem odd to count anniversaries in months, the speed of the advances in data science makes just a few months seem like years. At the 2017 RSNA meeting in November, the enthusiasm for learning more about artificial intelligence (AI) in radiological care was palpable, and the ACR DSI was well represented in the RSNA Machine Learning Showcase to share our work with RSNA attendees and industry leaders.

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Learning the Language of AI

Radiologists must learn the language of AI to make a successful payment policy case.
By Ezequiel Silva III, MD, FACR | Physician | Jan. 23, 2018
Radiologists must learn the language of AI to make a successful payment policy case

Artificial intelligence (AI) has its own language. So does economics. I feel pretty confident with econ-speak and can throw out phrases like intensity of work or acronyms like CPT, HOPPS, and QPP in rapid fire. But I am not as well-versed in the language of AI — a point that became apparent during a recent “Economics of AI” talk I gave to a room full of radiology AI experts.

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Beyond Interpretation

Artificial intelligence will do more than identify findings to increase radiologists’ value.
By Woojin Kim, MD | Physician | Dec. 14, 2017
Artificial intelligence will do more than identify findings to increase radiologists value

Today, plenty of hope, fear, and hype surround the use of artificial intelligence (AI) in radiology. With media attention and many startups focused on using AI to identify findings within medical images, it’s easy for us in the radiology profession to have "tunnel vision" about AI in our field. However, it’s important to widen our aperture to see the many other ways AI can benefit medical imaging.

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Entering the Real World of Artificial Intelligence

Integrating artificial intelligence into radiology is not as simple as it appears.
By Raym Geis, MD, FACR | Physician | Nov. 20, 2017
Entering the Real World of Artificial Intelligence

If you’ve ever used the search program on your smartphone to find all your photos of a special person or your pet, you are already using artificial intelligence (AI) for image interpretation

While it looks like magic, AI programs that differentiate photos of cats from dogs, and even your own pet from others, are usually based on conventional mathematical optimization.

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Getting Acquainted with AI in Medical Imaging

A list of resources curated by an IT manager provides a starting point.
By John Gagnon | IT Manager | Nov. 3, 2017
Getting Acquainted with AI in Medical Imaging

So you want to learn about Artificial Intelligence (AI) but don’t know where to start? A Google search for “resources for artificial intelligence” yields more than 25 million results, so it’s understandable why you might feel overwhelmed. Adding “in radiology” prunes the list down to an only slightly less cumbersome 459,000 results. What follows is a brief collection of resources culled from these nearly half-million hits — a starting point to help you learn the basics of AI in medical imaging.

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AI in Imaging: A Patient’s Perspective

A patient wants radiologists to remain involved in AI era.
By David Andrews | Patient | Oct. 4, 2017
AI in Imaging: A Patient’s Perspective

To explain how I view artificial intelligence (AI) in medicine, I like to use car repair as an analogy. As car repair is about vehicle maintenance, medicine is, in essence, about the maintenance and repair of people.

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Imaging 3.0 Meets Artificial Intelligence

Artificial intelligence provides another tool in the Imaging 3.0 toolkit.
By Bibb Allen Jr., MD, FACR | Physician | Sept. 20, 2017
Imaging 3.0 Meets Artificial Intelligence

For the past five years, ACR’s Imaging 3.0 initiative has been the toolkit that we, as radiologists, have used to enhance our value beyond our interpretations to be better stewards of imaging appropriateness, provide a more patient-centered focus within our practices, and prepare for the evolution of healthcare financing and federal payment policy. Imaging 3.0 continues to challenge us to take ownership of our patients’ entire imaging experience, and now, we have a new tool in the kit that will help us further increase the value we bring to patient care at each step in the imaging value chain: artificial intelligence (AI).

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The Future Radiologist

With the advent of artificial intelligence, the best radiologists will no longer be those with the sharpest eyes.
By Arun Krishnaraj, MD, MPH | Physician | Sept. 6, 2017
The Future Radiologist

Dr. Abadi enters the dimly lit reading room for the first time since her medical student rotations in radiology. After a grueling intern year in surgery, she appreciates the relative calm of the reading room and looks forward to beginning her radiology residency. As she logs into her workstation for the first time, she turns to an upper-level resident and asks, “So who’s the best radiologist in the department?”

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I’m Your AI Assistant: How Can I Help?

AI Assistant blog offers valuable information and insights about AI in medical imaging.
By Bibb Allen Jr., MD, FACR | Physician | Aug. 23, 2017
I’m Your AI Assistant: How Can I Help?
AI Assistant Blog

Around the turn of the 20th century, Nikola Tesla, the Serbian-American inventor well known to radiologists and radiation oncologists as a physicist and futurist, made a bold prediction about how technology and humans would one day coexist. He said, “In the 21st century, the robot will take the place which slave labor occupied in ancient civilization.”

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