Radiology grapples with looming machine learning ‘threat’
Machine learning is quickly becoming a game changer within radiology. The reaction is a mixed bag—some are concerned artificial intelligence will impact their job security while others see it as a net positive.
Fourth year radiology fellow Phelps Kelley told NPR his biggest concern is being replaced by artificial intelligence. Despite some pushback, many radiologists welcome the new development—and in some cases, believe they will benefit from it.
UCSF radiologist Dr. Marc Kohli, along with colleague Dr. John Mongan are advocates of machine learning and are currently exploring the best use of artificial intelligence and algorithms within radiology.
Mongan believes the algorithms could help him and other radiologists prioritize patients and make sure they do not miss something. He thinks radiologists will spend less time looking at images and more time selecting algorithms and interpreting the results.
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As a senior news writer for TriMed, Subrata covers cardiology, clinical innovation and healthcare business. She has a master’s degree in communication management and 12 years of experience in journalism and public relations.