Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing.

We built a natural language processing (NLP) method to automatically extract clinical findings in radiology reports and characterize their level of change and significance according to a radiology-specific information model. We utilized a combination of machine learning and rule-based approaches for...

Full description

Bibliographic Details

Published in:	Journal of Digital Imaging Vol. 30; no. 3; pp. 314 - 323
Main Authors:	Hassanpour, Saeed, Bay, Graham, Langlotz, Curtis
Format:	tables/charts Journal Article
Published:	Springer Nature Jun2017
Online Access:	View this record in EBSCOhost