How radiology reporting software has evolved from spell check to AI
Copyright: rsna.org – “Speech Recognition Technology Shows Promise for Better Radiology Reports”
Speech recognition technology has been used in radiology reporting for well over two decades, with varying degrees of accuracy, but new developments are helping radiologists in ways far beyond traditional dictation.
Early speech recognition software required a lot of training of both the software and the radiologist, who often had to review the final text to correct errors due to mis-transcribed words, omitted words, inaccuracy transcribing non-American English accents, background noise, and both specialized medical and non-medical lay terms that the software did not recognize.
“When speech recognition technology first came out for radiology transcription it was not much more than a simple text editor—a spell checker was probably the most useful add-on feature, but there was nothing available that checked your content or syntax for other kinds of errors” said Adam Flanders, MD, professor of neuroradiology/ENT radiology and vice chair, imaging informatics at the Thomas Jefferson University in Philadelphia. “Many of us remember that before full speech recognition became standard practice, we would often rely on savvy medical transcriptionists to identify errors and omissions, flag the report and send it back for corrections before releasing it. Without human transcriptionists, the responsibility for final content and syntax checks fell fully to the radiologist.”
Whatever its continuing challenges, speech recognition software is nearly universally accepted and developments in the technology are helping further augment it in supporting standardized radiology reports.
“The ultimate goal is to make radiology reporting more efficient, error-free and concise without burdening the radiologist with new tasks. Instead, next generation reporting systems would work in conjunction with the radiologist.”
ADAM FLANDERS, MD
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