Using BERT Models to Label Radiology Reports
Author:
Affiliation:
1. From the Department of Radiology, New York Presbyterian–Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032.
Publisher
Radiological Society of North America (RSNA)
Subject
Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
http://pubs.rsna.org/doi/pdf/10.1148/ryai.220124
Reference6 articles.
1. Exploring Large-scale Public Medical Image Datasets
2. Practical Guide to Natural Language Processing for Radiology
3. Performance of Multiple Pretrained BERT Models to Automate and Accelerate Data Annotation for Large Datasets
4. Supervised and unsupervised language modelling in Chest X-Ray radiological reports
5. Detecting insertion, substitution, and deletion errors in radiology reports using neural sequence-to-sequence models
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