Podcast: Improving Natural Language Processing Error Rates
C. Matthew Hawkins, MD, discusses challenges of natural language processing and how more standardization can reduce error rates of speech recognition software.
[[{"type":"media","view_mode":"media_crop","fid":"11967","attributes":{"alt":"","class":"media-image media-image-right","id":"media_crop_7562901937715","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"207","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"margin: 5px; float: right; border-width: 0px; border-style: solid;","title":" ","typeof":"foaf:Image"}}]]As many as 22 percent of radiology reports contain errors associated with natural language processing, said C. Matthew Hawkins, MD, a pediatric radiology fellow at Cincinnati Children’s Hospital Medical Center. Hawkins is speaking on the topic at the SIIM 2012 conference in Orlando this week.
In this podcast, Hawkins discusses how these errors can change the meaning of radiology reports and how augmenting standardized content associated with various types of speech recognition software can decrease mistakes.
GE HealthCare Debuts AI-Powered Cardiac CT Device at ACC Conference
April 1st 2025Featuring enhanced low-dose image quality with motion-free images, the Revolution Vibe CT system reportedly facilitates improved diagnostic clarity for patients with conditions ranging from in-stent restenosis to atrial fibrillation.
The Reading Room Podcast: Current Perspectives on the Updated Appropriate Use Criteria for Brain PET
March 18th 2025In a new podcast, Satoshi Minoshima, M.D., Ph.D., and James Williams, Ph.D., share their insights on the recently updated appropriate use criteria for amyloid PET and tau PET in patients with mild cognitive impairment.
