Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition

11/05/2019
by   Hamada A. Nayel, et al.
0

In recent years, Deep Learning (DL) models are becoming important due to their demonstrated success at overcoming complex learning problems. DL models have been applied effectively for different Natural Language Processing (NLP) tasks such as part-of-Speech (PoS) tagging and Machine Translation (MT). Disease Named Entity Recognition (Disease-NER) is a crucial task which aims at extracting disease Named Entities (NEs) from text. In this paper, a DL model for Disease-NER using dictionary information is proposed and evaluated on National Center for Biotechnology Information (NCBI) disease corpus and BC5CDR dataset. Word embeddings trained over general domain texts as well as biomedical texts have been used to represent input to the proposed model. This study also compares two different Segment Representation (SR) schemes, namely IOB2 and IOBES for Disease-NER. The results illustrate that using dictionary information, pre-trained word embeddings, character embeddings and CRF with global score improves the performance of Disease-NER system.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/07/2018

microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF

For named entity recognition (NER), bidirectional recurrent neural netwo...
research
08/15/2019

Improving Multi-Word Entity Recognition for Biomedical Texts

Biomedical Named Entity Recognition (BioNER) is a crucial step for analy...
research
10/24/2020

Disease Normalization with Graph Embeddings

The detection and normalization of diseases in biomedical texts are key ...
research
10/20/2018

Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings

Recently, due to the increasing popularity of social media, the necessit...
research
08/11/2017

Unified Neural Architecture for Drug, Disease and Clinical Entity Recognition

Most existing methods for biomedical entity recognition task rely on exp...
research
04/19/2016

Exploring Segment Representations for Neural Segmentation Models

Many natural language processing (NLP) tasks can be generalized into seg...
research
07/01/2020

Improving NER for Clinical Texts by Ensemble Approach using Segment Representations

Clinical Named Entity Recognition (Clinical-NER), which aims at identify...

Please sign up or login with your details

Forgot password? Click here to reset