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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.
New Study Examines Short-Term Consistency of Large Language Models in Radiology
November 22nd 2024While GPT-4 demonstrated higher overall accuracy than other large language models in answering ACR Diagnostic in Training Exam multiple-choice questions, researchers noted an eight percent decrease in GPT-4’s accuracy rate from the first month to the third month of the study.
FDA Grants Expanded 510(k) Clearance for Xenoview 3T MRI Chest Coil in GE HealthCare MRI Platforms
November 21st 2024Utilized in conjunction with hyperpolarized Xenon-129 for the assessment of lung ventilation, the chest coil can now be employed in the Signa Premier and Discovery MR750 3T MRI systems.
FDA Clears AI-Powered Ultrasound Software for Cardiac Amyloidosis Detection
November 20th 2024The AI-enabled EchoGo® Amyloidosis software for echocardiography has reportedly demonstrated an 84.5 percent sensitivity rate for diagnosing cardiac amyloidosis in heart failure patients 65 years of age and older.
