Read by QxMD icon Read


Licong Cui, Wei Zhu, Shiqiang Tao, James T Case, Olivier Bodenreider, Guo-Qiang Zhang
Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT. Material and Methods: All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm. Four lexical patterns (the lexical part) are identified among the extracted non-lattice subgraphs...
February 19, 2017: Journal of the American Medical Informatics Association: JAMIA
Xiaonan Ji, Alan Ritter, Po-Yin Yen
OBJECTIVE: Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies...
March 13, 2017: Journal of Biomedical Informatics
Christopher Ochs, James T Case, Yehoshua Perl
Thousands of changes are applied to SNOMED CT's concepts during each release cycle. These changes are the result of efforts to improve or expand the coverage of health domains in the terminology. Understanding which concepts changed, how they changed, and the overall impact of a set of changes is important for editors and end users. Each SNOMED CT release comes with delta files, which identify all of the individual additions and removals of concepts and relationships. These files typically contain tens of thousands of individual entries, overwhelming users...
February 12, 2017: Journal of Biomedical Informatics
Wilfred Bonney, James Galloway, Christopher Hall, Mikhail Ghattas, Leandro Tramma, Thomas Nind, Louise Donnelly, Emily Jefferson, Alexander Doney
Background & Objectives: Legacy laboratory test codes make it difficult to use clinical datasets for meaningful translational research, where populations are followed for disease risk and outcomes over many years. The Health Informatics Centre (HIC) at the University of Dundee hosts continuous biochemistry data from the clinical laboratories in Tayside and Fife dating back as far as 1987. However, the HIC-managed biochemistry dataset is coupled with incoherent sample types and unstandardised legacy local test codes, which increases the complexity of using the dataset for reasonable population health outcomes...
2017: Studies in Health Technology and Informatics
Min Sook Park, Zhe He, Zhiwei Chen, Sanghee Oh, Jiang Bian
BACKGROUND: The widely known terminology gap between health professionals and health consumers hinders effective information seeking for consumers. OBJECTIVE: The aim of this study was to better understand consumers' usage of medical concepts by evaluating the coverage of concepts and semantic types of the Unified Medical Language System (UMLS) on diabetes-related postings in 2 types of social media: blogs and social question and answer (Q&A). METHODS: We collected 2 types of social media data: (1) a total of 3711 blogs tagged with "diabetes" on Tumblr posted between February and October 2015; and (2) a total of 58,422 questions and associated answers posted between 2009 and 2014 in the diabetes category of Yahoo! Answers...
November 24, 2016: JMIR Medical Informatics
L F Soualmia, J Charlet
OBJECTIVES: To summarize excellent current research in the field of Knowledge Representation and Management (KRM) within the health and medical care domain. METHOD: We provide a synopsis of the 2016 IMIA selected articles as well as a related synthetic overview of the current and future field activities. A first step of the selection was performed through MEDLINE querying with a list of MeSH descriptors completed by a list of terms adapted to the KRM section. The second step of the selection was completed by the two section editors who separately evaluated the set of 1,432 articles...
November 10, 2016: Yearbook of Medical Informatics
Pablo López-García, Stefan Schulz
Unprincipled modeling decisions in large-domain ontologies, such as SNOMED CT, are problematic and might act as a barrier for their quality assurance and successful use in electronic health records. Most previous work has focused on clustering problematic concepts, which is helpful for quality control but faces difficulties in pinpointing the origin of those modeling problems. In this study, we examined the underlying structural patterns in SNOMED CT's data model as such patterns directly reflect the modeling strategies of editors...
2016: PloS One
Wenxin Ning, Ming Yu, Dehua Kong
BACKGROUND: Semantic similarity estimation significantly promotes the understanding of natural language resources and supports medical decision making. Previous studies have investigated semantic similarity and relatedness estimation between biomedical terms through resources in English, such as SNOMED-CT or UMLS. However, very limited studies focused on the Chinese language, and technology on natural language processing and text mining of medical documents in China is urgently needed...
December 2016: Journal of Biomedical Informatics
Guangming Xing, Guo-Qiang Zhang, Licong Cui
BACKGROUND: Redundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). Each redundant relation represents a possibly unintended defect that needs to be corrected in the ontology quality assurance process. Detecting and eliminating redundant relations would help improve the results of all methods relying on the relevant ontological systems as knowledge source, such as the computation of semantic distance between concepts and for ontology matching and alignment...
2016: BioData Mining
María Del Mar Roldán-García, María Jesús García-Godoy, José F Aldana-Montes
BACKGROUND: Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) has been designed as standard clinical terminology for annotating Electronic Health Records (EHRs). EHRs textual information is used to classify patients' diseases into an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) category (usually by an expert). Improving the accuracy of classification is the main purpose of using ontologies and OWL representations at the core of classification systems...
October 13, 2016: Journal of Biomedical Semantics
J T Helgstrand, N Klemann, M A Røder, B G Toft, K Brasso, B Vainer, P Iversen
BACKGROUND: Systematized Nomenclature of Medicine (SNOMED) codes are computer-processable medical terms used to describe histopathological evaluations. SNOMED codes are not readily usable for analysis. We invented an algorithm that converts prostate SNOMED codes into an analyzable format. We present the methodology and early results from a new national Danish prostate database containing clinical data from all males who had evaluation of prostate tissue from 1995 to 2011. MATERIALS AND METHODS: SNOMED codes were retrieved from the Danish Pathology Register...
2016: Clinical Epidemiology
Elizabeth Craig, Neal Kerr, Gabrielle McDonald
AIM: In New Zealand, there is a paucity of information on children with chronic conditions and disabilities (CCD). One reason is that many are managed in hospital outpatients where diagnostic coding of health-care events does not occur. This study explores the feasibility of coding paediatric outpatient data to provide health planners with information on children with CCD. METHODS: Thirty-seven clinicians from six District Health Boards (DHBs) trialled coding over 12 weeks...
October 7, 2016: Journal of Paediatrics and Child Health
Hadyl Asfari, Julien Souvignet, Agnès Lillo-Le Louët, Béatrice Trombert, Marie-Christine Jaulent, Cédric Bousquet
AIM: To propose an alternative approach for building custom groupings of terms that complements the usual approach based on both hierarchical method (selection of reference groupings in medical dictionary for regulatory activities [MedDRA]) and/or textual method (string search), for case reports extraction from a pharmacovigilance database in response to a safety problem. Here we take cardiac valve fibrosis as an example. METHODS: The list of terms obtained by an automated approach, based on querying ontology of adverse drug reactions (OntoADR), a knowledge base defining MedDRA terms through relationships with systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts, was compared with the reference list consisting of 53 preferred terms obtained by hierarchical and textual method...
July 21, 2016: Thérapie
Begoña Martínez-Salvador, Mar Marcos, Alejandro Mañas, José Alberto Maldonado, Monserrat Robles
Clinical decision-support systems (CDSSs) should be able to interact with the electronic health record (EHR) to obtain the patient data they require. A recent solution for the interoperability of CDSSs and EHR systems consists in the use of a mediated schema which provides a unified view of their two schemas. The use of such a mediated schema requires the definition of a mapping between this schema and the EHR one. In this paper we investigate the use of the SNOMED CT Expression Constraint Language to characterize these mappings...
2016: Studies in Health Technology and Informatics
V M Giménez-Solano, J A Maldonado, S Salas-García, D Boscá, M Robles
The need to achieve high levels of semantic interoperability in the health domain is regarded as a crucial issue. Nowadays, one of the weaknesses when working in this direction is the lack of a coordinated use of information and terminological models to define the meaning and content of clinical data. IHTSDO is aware of this problem and has recently developed the SNOMED CT Expression Constraint Language to specify subsets of concepts. In this paper, we describe an implementation of an execution engine of this language...
2016: Studies in Health Technology and Informatics
Rainer Thiel, Strahil Birov, Klaus Piesche, Anne Randorff Højen, Kirstine Rosenbeck Gøeg, Heike Dewenter, Reza Fathollah Nejad, Sylvia Thun, Pim Volkert, Vesna Kronstein Kufrin, Veli Stroetmann
As part of its investigations, the EU-funded ASSESS CT project developed an Economic Assessment Model for assessing SNOMED CT's and other terminologies' socio-economic impact in a systematic approach. Methodology and key elements of the model are presented: cost and benefit indicators for assessing deployment, and a cost-benefit analysis tool to collect, estimate, and evaluate data.
2016: Studies in Health Technology and Informatics
Anne Randorff Højen, Dorthe Brønnum, Kirstine Rosenbeck Gøeg, Pia Britt Elberg
This paper presents an analysis of the extent to which SNOMED CT is suitable for representing data within the domain of head and neck cancer. In this analysis we assess whether the concept model of SNOMED CT comply with the documentation needed within this clinical domain. Attributes from the follow-up template of the clinical quality registry for Danish Head and Neck Cancer, and their respective value sets were mapped to SNOMED CT using existing mapping guidelines. Results show that post-coordination is important to represent specific types of value sets, such as absence of findings and severities...
2016: Studies in Health Technology and Informatics
Marzouk Mamou, Alan Rector, Stefan Schulz, James Campbell, Harold Solbrig, Jean-Marie Rodrigues
It is investigated whether the content of the Joint Linearization for Mortality and Morbidity Statistics of the 11th ICD revision can be semantically represented by formalisms acting on the clinical terminology SNOMED CT, viz. the IHTSDO Compositional Grammar (CG) and the Expression Constraint Language (ECL). Whereas CG provides a composition syntax for building coordinated SNOMED CT expressions, ECL provides a powerful query mechanism. Both formalisms can be leveraged to guarantee inter-operation between an ontology-based terminology like SNOMED CT and a statistical classification like ICD, characterized by single hierarchies and exhaustive, mutually exclusive classes...
2016: Studies in Health Technology and Informatics
Manuel Quesada-Martínez, Jesualdo Tomás Fernández-Breis, Daniel Karlsson
The number of biomedical ontologies has increased significantly in recent years. Many of such ontologies are the result of efforts of communities of domain experts and ontology engineers. The development and application of quality assurance (QA) methods should help these communities to develop useful ontologies for both humans and machines. According to previous studies, biomedical ontologies are rich in natural language content, but most of them are not so rich in axiomatic terms. Here, we are interested in studying the relation between content in natural language and content in axiomatic form...
2016: Studies in Health Technology and Informatics
Syed Sibte Raza Abidi, Abhinav Kumar Singh, Sean Christie
In this paper we present a framework for the semi-automatic extraction of medical entities from referral letters and use them to transcribe a case report form. Our framework offers the functionality to: (a) extract the medical entity from the unstructured referral letters, (b) classify them according to their semantic type, and (c) transcribe a case report form based on the extracted information from the referral letter. We take a semantic text analytics approach where SNOMED-CT ontology is used to both classify referral concepts and to establish semantic similarities between referral concepts and CRF elements...
2016: Studies in Health Technology and Informatics
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"