Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network-Reference-Cited by-同舟云学术

Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network

Published:2019-04 Issue:4 Volume:212 Page:734-740
ISSN:0361-803X
Container-title:American Journal of Roentgenology
language:en
Short-container-title:American Journal of Roentgenology

Author:

Lee Changhwan¹,Kim Yeesuk²,Kim Young Soo³,Jang Jongseong⁴

Affiliation:

1. Department of Biomedical Engineering, Hanyang University, Seoul, Korea.

2. Department of Orthopedic Surgery, College of Medicine, Hanyang University, Seoul, Korea.

3. Institute of Innovative Surgical Technology, Hanyang University, Seoul, Korea.

4. Center for Integration of Advanced Medicine Life Science Innovative Technologies, Department of Advanced Medical Initiatives, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka-shi, Fukuoka-ken 812-8582, Japan.

Publisher

American Roentgen Ray Society

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://www.ajronline.org/doi/pdf/10.2214/AJR.18.19869

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4. Active Computerized Pharmacovigilance Using Natural Language Processing, Statistics, and Electronic Health Records: A Feasibility Study

5. Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes

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