Title
An Ontology-Based Approach to Natural Language Generation from Coded Data in Electronic Health Records
Abstract
The worldwide adoption of the HL7 Clinical Document Architecture (CDA) is promoting the availability of coded data (CDA entries) within sections of clinical documents. At the moment, an increasing number of studies are investigating ways to transform the narratives of CDA documents into machine process able CDA entries. This paper addresses the reverse problem, i.e. obtaining linguistic representations (sentences) from CDA entries. The approach presented employs Natural Language Generation (NLG) techniques and deals with two major tasks: content selection and content expression. The current research proposes a formal semantic representation of CDA entries and investigates how expressive domain ontologies in OWL and SPARQL SELECT queries can contribute to NLG. To validate the proposal, the study has focused on CDA entries from the History of Present Illness sections of CDA consultation notes. The results obtained are encouraging, as the clinical narratives automatically generated from these CDA entries fulfil the clinicians' expectations.
Year
DOI
Venue
2011
10.1109/EMS.2011.47
EMS
Keywords
Field
DocType
coded data,cda entry,electronic health records,cda document,clinical narrative,content selection,able cda entry,natural language generation,hl7 clinical document architecture,clinical document,content expression,cda consultation note,ontology-based approach,formal semantics,natural language processing,ontology,semantic web,owl,sparql
Ontology (information science),Natural language generation,Ontology,Information retrieval,Computer science,Semantic Web,Narrative,SPARQL,Natural language processing,Artificial intelligence,Delegation (computing),Clinical Document Architecture
Conference
ISSN
ISBN
Citations 
2473-3539
978-1-4673-0060-5
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
M. Arguello101.01
Julio Des2273.50
Maria Jesus Fernandez Prieto3285.55
Perez, R.400.34
S. Lekkas500.34