Faculty, Staff and Student Publications

Publication Date

1-1-2018

Journal

American Medical Informatics Association Annual Symposium

Abstract

We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. The system consists of two constituent sequence classifiers: a frame identification (lexical unit) classifier and a frame element classifier. The classifier achieves an F

Keywords

Datasets as Topic, Deep Learning, Electronic Health Records, Heuristics, Humans, Information Storage and Retrieval, Natural Language Processing, Neoplasms, Neural Networks, Computer, Semantics

PMID

30815198

PMCID

PMC6371330

PubMedCentral® Posted Date

December 2018

PubMedCentral® Full Text Version

Post-Print

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.