At the RSNA 2016 annual meeting, the biggest trend in radiology was Deep Learning. TMTG asked four senior global VPs of cross-modality strategy and innovation at leading imaging OEMs one simple question:
The unanimous answer was that the implementation of deep learning algorithms in image processing (if FDA cleared) would drastically reduce the need for radiologists to read images and may replace those tasks altogether. The reduction of routine image interpretation tasks will drastically transform radiologists’ roles.
The Rise of Artificial Intelligence in Radiology
Deep learning algorithms poised to hit the market could select and extract features from medical images as well as identify, classify and quantify disease patterns with minimal, if any, input from radiologists. Three of the executives felt that the radiologists’ role in image reading would be morphed into merely overseeing the technology and providing assistance on difficult diagnoses. One of the four executives felt that pattern recognition technology could completely supplant radiologists as image readers within the next two decades.
The VPs all agreed that this technology is imminent. Deep learning algorithms have already been implemented in imaging technologies in other industries. The only remaining hurdle to AI software for medical applications is government approval. It’s not a matter of if Deep Learning algorithms will disrupt the market, but when.
Radiologists’ New Role
Given the impending disruption in radiology from Deep Learning algorithms, professionals should look forward to adjustments in what it means to be a radiologist. TMTG has identified a transition away from siloed radiology departments, departments primarily focused on modality-specific image interpretation and specialization by body part. The executives with whom we spoke hypothesize that future radiologists’ roles will be enhanced and integrated further into care teams. Radiologists will become disease consultants with a clinical focus like oncology, cardiology, etc. This new role will allow radiologists to focus more on providing recommendations for pre- or post-imaging care decisions while having a much greater influence in improving patient outcomes.
Learn more about the redefinition of radiology in this changing environment from Dr. Paul Chang of the University of Chicago.
To judge how the industry will react to disruptions such as Deep Learning, The MarkeTech Group keeps our finger on the pulse of radiology with regular feedback from our imagePRO panel. This valuable voice-of-customer data helps to predict trends, position products, and analyze the acceptance of new innovations like AI and Deep Learning in a changing medical imaging market. How can we help you act on these trends?
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Christian Renaudin, D.V.M., Ph. D.
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