Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
http://link.springer.com/content/pdf/10.1007/s10278-019-00234-y.pdf
Reference13 articles.
1. Rubin DL, Kahn, Jr CE: Common Data Elements in Radiology. Radiology 283:837–844, 2017
2. European Society of Radiology (ESR): ESR paper on structured reporting in radiology. Insights Imaging 9(1):1–7, 2018
3. Singh S: Natural Language Processing for Information Extraction. arXiv [cs.CL], 2018
4. Hassanpour S, Langlotz CP: Information extraction from multi-institutional radiology reports. Artif Intell Med 66:29–39, 2016
5. Nandhakumar N, Sherkat E, Milios EE, Gu H, Butler M: Clinically Significant Information Extraction from Radiology Reports. In: Proceedings of the 2017 ACM Symposium on Document Engineering - DocEng ’17. ACM Press, 2017, pp 153–162
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