On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.
Journal:
Journal of biomedical informatics
Published Date:
Jun 30, 2015
Abstract
The advances achieved in Natural Language Processing make it possible to automatically mine information from electronically created documents. Many Natural Language Processing methods that extract information from texts make use of annotated corpora, but these are scarce in the clinical domain due to legal and ethical issues. In this paper we present the creation of the IxaMed-GS gold standard composed of real electronic health records written in Spanish and manually annotated by experts in pharmacology and pharmacovigilance. The experts mainly annotated entities related to diseases and drugs, but also relationships between entities indicating adverse drug reaction events. To help the experts in the annotation task, we adapted a general corpus linguistic analyzer to the medical domain. The quality of the annotation process in the IxaMed-GS corpus has been assessed by measuring the inter-annotator agreement, which was 90.53% for entities and 82.86% for events. In addition, the corpus has been used for the automatic extraction of adverse drug reaction events using machine learning.
Authors
Keywords
Adverse Drug Reaction Reporting Systems
Algorithms
Automation
Data Mining
Drug-Related Side Effects and Adverse Reactions
Electronic Health Records
Language
Linguistics
Machine Learning
Natural Language Processing
Pharmaceutical Preparations
Pharmacovigilance
Predictive Value of Tests
Reproducibility of Results
Translating