AJR Podcast: Artificial Intelligence as a Radiology Safety Net

AJR podcast with guest Dr. Ben Strong, vRad CMO

vRad’s Chief Medical Officer, Dr. Ben Strong, sat down with radiologist Dr. Francis Deng, of Johns Hopkins—and host of the AJR Podcast Series on Diagnostic Excellence and Error—to talk about the use of artificial intelligence within quality assurance and AI’s evolving impact on diagnostic error and malpractice risk.

Listen to the full podcast here:

A few podcast highlights:

The “Big 5” AI algorithms (1:00)

Dr. Strong shares his deep-dive analysis of internal QA data and closed malpractice claims, which identified five pathologies most often linked to major diagnostic errors or high indemnity costs: aortic dissection, spinal epidural abscess, superior mesenteric artery occlusion, pulmonary embolism, and intracranial hemorrhage. This analysis, and the opportunity for quality improvements, were instrumental in prioritizing these pathologies in vRad’s AI model development.

Elevating quality assurance with AI (14:00)

Dr. Deng and Dr. Strong explore the process vRad is using to leverage AI to identify diagnostic errors within a quality assurance program, enabling rapid correction to reduce patient impact.

NLP: the most underrated AI tool in radiology? (16:15)

Dr. Strong emphasizes that natural language processing (NLP), a subset of artificial intelligence, may have done more to improve quality of care at vRad than even the image-detection algorithms.

Learn more about how vRad is driving higher-quality care with AI technology.