In a new podcast episode, Joseph Cavallo, MD, MBA, offered his perspective on AI integration, potential efficiency gains, navigating post-deployment monitoring and how to incorporate AI literacy into radiology resident training.
|Slideshows|October 16, 2014
When Radiologists Don’t Want to be Radiologists
Author(s)Deborah Abrams Kaplan
How three radiology-trained professionals made their careers outside of the reading room. Hint: they are all in the C-suite.
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You may have dreamed of being a radiologist since you were a kid. Or maybe you have competing interests, and always wanted to start a business, invent devices, consult, or dip your toes into another career pool. Given the shaky radiology job market, maybe it’s time to take action on those dreams.Diagnostic Imaging spoke with three radiology-trained entrepreneurs who did just that: started new businesses while continuing to use and capitalizing on their physician training. Check out our slideshow to see what they’re doing.
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In the third of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss recent developments with autonomous AI in breast imaging and share their perspective on the overall potential of AI to help mitigate the radiologist shortage.
In the second of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss how to handle disagreements with adjunctive AI in breast imaging, whether to include AI assessments in PACS, and whether patients should pay for the use of adjunctive AI.
Has the barrage of passwords, PINs and authenticator apps gone around the bend to a point where it hampers efficiency and productivity?
Catch up on the top radiology content of the past week.
In a recent interview with Diagnostic Imaging, Joseph Cavallo, MD, MBA, offered insights on post-deployment monitoring with AI, the potential for improved workflow efficiency and the ongoing challenge of balancing essential clinical skills and AI literacy in the training of radiology residents and fellows.
The FFR-IQ software recently demonstrated a 92.2 percent sensitivity for non-invasive estimation of fractional flow reserve (FFRC) based on coronary CT angiography (CCTA) scans.
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