Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging
Nooshin Abbasi, Ronilda Lacson, Neena Kapoor, Andro Licaros, Jeffrey P. Guenette, Kristine S. Burk, Mark M. Hammer, Sonali Desai, Sunil Eappen, Sanjay Saini, Ramin Khorasani
Abstract
BACKGROUND. Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potential for identifying RAIs and thereby assisting large-scale quality improvement efforts.
Topics & Concepts
MedicineTest setArtificial intelligenceContext (archaeology)Machine learningTest (biology)Medical physicsComputer sciencePaleontologyBiologyArtificial Intelligence in Healthcare and EducationRadiology practices and educationRadiomics and Machine Learning in Medical Imaging