Find out how Associate Professor Frank Gaillard’s Radiopaedia.org is changing the way medicine is taught and his views on how technology is changing the medical landscape.
Frank Gaillard is the inspirational force behind Radiopaedia.org, one of the world’s largest compilations of Radiology reference articles, images and clinical cases. Material is freely added and edited by registered users and frequently reviewed by Radiologists, Radiology residents and registrars, changing the way medicine is taught all around the world.
We partnered with Radiopaedia at the #RANZCR2018 ASM to bring delegates our “Diagnosis Contest” which was a lot of fun. We took the opportunity to catch up with Frank at the event in Canberra to find out how his open source radiology resource is shaking up medical education globally and what impact it’s having on the radiology community now and into the future.
Your mission to create the most comprehensive radiology resource and make it available to the world for free is inspirational. Can you provide examples of how the resources directly impact doctors in training? In other words, how do you think Radiopaedia is helping radiologists?
Every week we receive numerous emails from users throughout the world explaining what Radiopaedia means to them. Just last week we received one from a dental student in northern Pakistan who explained she has no access whatsoever to formal Radiology teaching. Instead, she learns off the x-rays taken during patient management and often misdiagnoses because of poor understanding.
She went on to say, "When I found out about Radiopaedia I remember staying up hours just scrolling through the cases to learn more because it changed the way I saw x-rays. It was like I was seeing differently, but with the same set of eyes!"
For me, this really captures what Radiopaedia is all about. It’s not just a hobby or a novelty. It’s now the cornerstone of radiology education for tens of thousands of training and practising health professionals around the world, particularly in the countries that need it the most.
Can you share with us an instance where one of the cases on Radiopaedia helped spread awareness about a particular condition or impacted diagnosis for the radiology community?
I don’t have one specific case, however, we hear all the time from our readers who encounter a real-life example of a pathology they’d only seen for the first time the day before on our site, or on our case-of-the-day posted on Facebook or Twitter. Along with many other progressive educational resources, we understand how important it is to disseminate educational material in small building blocks which facilitates constant incremental education. Social media, for all its problems and failings, nonetheless offers a tremendous opportunity to make ongoing education something that happens throughout the course of every day rather than just dedicated 'study time'.
Do you think technology will impact radiologists’ responsibilities in the future? If so, what do you think will have the greatest impact?
Machine Learning (ML) is the obvious and much-talked-about game-changer we’re all going to deal with over the next 10-25 years. No one really knows the size or character of the impact ML will have on our profession and therefore what the role of a radiologist in 2030 or 2050 will look like. There are a large number of self-professed experts giving very divergent predictions and although no doubt some will be proven right in the long term, I don't think that’s necessarily because they have seen further than others.
Predicting the future is a tricky business unless you make a large number of predictions; as the saying goes, "even a blind squirrel will occasionally find a nut". But that won't stop me putting in my two cents worth. I think a radiologist of 2050 will be about as far removed as we are from a radiologist of 1950 and it’s difficult to believe our ability to correctly identify and interpret pathology won't be greatly enhanced by ML-powered algorithms.
This isn’t particularly controversial. The controversy is about what role will be left for humans to perform. My feeling is if the thing you mostly do as a radiologist is spot abnormalities and mention a few common likely causes for that appearance, then yes, algorithms will be able to do most of that fairly soon.
If, however, you’re interventional or a subspecialist, or an integral part of a multidisciplinary team involved in the care of patients beyond just looking at their images, then it will take a lot longer to replace you with a small plastic box. This is especially true if you embrace these new technologies, understand their strengths and limitations and use them to augment your contribution to patient care.
We look forward to following Radiopaedia’s progress into the future.
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