scholarly journals An Upper-Level Ontology for the Biomedical Domain

2003 ◽  
Vol 4 (1) ◽  
pp. 80-84 ◽  
Author(s):  
Alexa T. McCray
Keyword(s):  
Clinical Medicine ◽  
Semantic Network ◽  
Biomedical Domain ◽  
Unified Medical Language System ◽  
Medical Language ◽  
The Us ◽  
Working Together ◽  
Broad Domain ◽  
Semantic Types ◽  
Upper Level

At the US National Library of Medicine we have developed the Unified Medical Language System (UMLS), whose goal it is to provide integrated access to a large number of biomedical resources by unifying the vocabularies that are used to access those resources. The UMLS currently interrelates some 60 controlled vocabularies in the biomedical domain. The UMLS coverage is quite extensive, including not only many concepts in clinical medicine, but also a large number of concepts applicable to the broad domain of the life sciences. In order to provide an overarching conceptual framework for all UMLS concepts, we developed an upper-level ontology, called the UMLS semantic network. The semantic network, through its 134 semantic types, provides a consistent categorization of all concepts represented in the UMLS. The 54 links between the semantic types provide the structure for the network and represent important relationships in the biomedical domain. Because of the growing number of information resources that contain genetic information, the UMLS coverage in this area is being expanded. We recently integrated the taxonomy of organisms developed by the NLM's National Center for Biotechnology Information, and we are currently working together with the developers of the Gene Ontology to integrate this resource, as well. As additional, standard, ontologies become publicly available, we expect to integrate these into the UMLS construct.

scholarly journals Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies

2016 ◽  
Vol 55 (02) ◽  
pp. 158-165 ◽  
Author(s):  
Y. Chen ◽  
Z. He ◽  
M. Halper ◽  
L. Chen ◽  
H. Gu
Keyword(s):  
Quality Assurance ◽  
Error Rate ◽  
Semantic Network ◽  
Snomed Ct ◽  
Semantic Type ◽  
Domain Experts ◽  
Unified Medical Language System ◽  
Type Assignment ◽  
Semantic Types ◽  
High Level

SummaryBackground: The Unified Medical Language System (UMLS) is one of the largest biomedical terminological systems, with over 2.5 million concepts in its Metathesaurus repository. The UMLS’s Semantic Network (SN) with its collection of 133 high-level semantic types serves as an abstraction layer on top of the Metathesaurus. In particular, the SN elaborates an aspect of the Metathesaurus’s concepts via the assignment of one or more types to each concept. Due to the scope and complexity of the Metathesaurus, errors are all but inevitable in this semantic-type assignment process.Objectives: To develop a semi-automated methodology to help assure the quality of semantic-type assignments within the UMLS.Methods: The methodology uses a cross- validation strategy involving SNOMED CT’s hierarchies in combination with UMLS se -mantic types. Semantically uniform, disjoint concept groups are generated programmatically by partitioning the collection of all concepts in the same SNOMED CT hierarchy according to their respective semantic-type assignments in the UMLS. Domain experts are then called upon to review the concepts in any group having a small number of concepts. It is our hypothesis that a semantic-type assignment combination applicable only to a very small number of concepts in a SNOMED CT hierarchy is an indicator of potential problems.Results: The methodology was applied to the UMLS 2013AA release along with the SNOMED CT from January 2013. An overall error rate of 33% was found for concepts proposed by the quality-assurance methodology. Supporting our hypothesis, that number was four times higher than the error rate found in control samples.Conclusion: The results show that the quality-assurance methodology can aid in effective and efficient identification of UMLS semantic-type assignment errors.

Query Log Analysis in Biomedicine

2011 ◽  
pp. 359-377 ◽  
Author(s):  
Elmer V. Bernstam ◽  
Jorge R. Herskovic ◽  
William R. Hersh
Keyword(s):  
Biomedical Literature ◽  
Log Analysis ◽  
Biomedical Domain ◽  
Medical Subject Headings ◽  
Biomedical Knowledge ◽  
Query Log ◽  
Query Log Analysis ◽  
Unified Medical Language System ◽  
Medical Language ◽  
Query Logs

Clinicians, researchers and members of the general public are increasingly using information technology to cope with the explosion in biomedical knowledge. This chapter describes the purpose of query log analysis in the biomedical domain as well as features of the biomedical domain such as controlled vocabularies (ontologies) and existing infrastructure useful for query log analysis. We focus specifically on MEDLINE, which is the most comprehensive bibliographic database of the world’s biomedical literature, the PubMed interface to MEDLINE, the Medical Subject Headings vocabulary and the Unified Medical Language System. However, the approaches discussed here can also be applied to other query logs. We conclude with a look toward the future of biomedical query log analysis.

scholarly journals The Unified Medical Language System

1993 ◽  
Vol 02 (01) ◽  
pp. 41-51 ◽  
Author(s):  
B. L. Humphreys ◽  
A. T. McCray ◽  
D. A. B. Lindberg
Keyword(s):  
High Speed ◽  
Semantic Network ◽  
High Capacity ◽  
Development Project ◽  
Successive Approximations ◽  
General Strategy ◽  
Language System ◽  
Unified Medical Language System ◽  
Medical Language ◽  
Timely Access

AbstractIn 1986, the National Library of Medicine began a long-term research and development project to build the Unified Medical Language System® (UMLS®). The purpose of the UMLS is to improve the ability of computer programs to “understand” the biomedical meaning in user inquiries and to use this understanding to retrieve and integrate relevant machine-readable information for users. Underlying the UMLS effort is the assumption that timely access to accurate and up-to-date information will improve decision making and ultimately the quality of patient care and research. The development of the UMLS is a distributed national experiment with a strong element of international collaboration. The general strategy is to develop UMLS components through a series of successive approximations of the capabilities ultimately desired. Three experimental Knowledge Sources, the Metathesaurus®, the Semantic Network, and the Information Sources Map have been developed and are distributed annually to interested researchers, many of whom have tested and evaluated them in a range of applications. The UMLS project and current developments in high-speed, high-capacity international networks are converging in ways that have great potential for enhancing access to biomedical information.

scholarly journals The Unified Medical Language System

1993 ◽  
Vol 32 (04) ◽  
pp. 281-291 ◽  
Author(s):  
B. L. Humphreys ◽  
A. T. McCray ◽  
D. A. B. Lindberg
Keyword(s):  
High Speed ◽  
Semantic Network ◽  
High Capacity ◽  
Development Project ◽  
Successive Approximations ◽  
General Strategy ◽  
Language System ◽  
Unified Medical Language System ◽  
Medical Language ◽  
Timely Access

AbstractIn 1986, the National Library of Medicine began a long-term research and development project to build the Unified Medical Language System® (UMLS®). The purpose of the UMLS is to improve the ability of computer programs to “understand” the biomedical meaning in user inquiries and to use this understanding to retrieve and integrate relevant machine-readable information for users. Underlying the UMLS effort is the assumption that timely access to accurate and up-to-date information will improve decision making and ultimately the quality of patient care and research. The development of the UMLS is a distributed national experiment with a strong element of international collaboration. The general strategy is to develop UMLS components through a series of successive approximations of the capabilities ultimately desired. Three experimental Knowledge Sources, the Metathesaurus®, the Semantic Network, and the Information Sources Map have been developed and are distributed annually to interested researchers, many of whom have tested and evaluated them in a range of applications. The UMLS project and current developments in high-speed, high-capacity international networks are converging in ways that have great potential for enhancing access to biomedical information.

scholarly journals Mapping the Gene Ontology Into the Unified Medical Language System

2004 ◽  
Vol 5 (4) ◽  
pp. 354-361 ◽  
Author(s):  
Jane Lomax ◽  
Alexa T. McCray
Keyword(s):  
Gene Ontology ◽  
Clinical Medicine ◽  
Gene Products ◽  
National Library ◽  
Web Based ◽  
Language System ◽  
Unified Medical Language System ◽  
Medical Language ◽  
Large Numbers ◽  
Go Terms

We have recently mapped the Gene Ontology (GO), developed by the Gene Ontology Consortium, into the National Library of Medicine's Unified Medical Language System (UMLS). GO has been developed for the purpose of annotating gene products in genome databases, and the UMLS has been developed as a framework for integrating large numbers of disparate terminologies, primarily for the purpose of providing better access to biomedical information sources. The mapping of GO to UMLS highlighted issues in both terminology systems. After some initial explorations and discussions between the UMLS and GO teams, the GO was integrated with the UMLS. Overall, a total of 23% of the GO terms either matched directly (3%) or linked (20%) to existing UMLS concepts. All GO terms now have a corresponding, official UMLS concept, and the entire vocabulary is available through the web-based UMLS Knowledge Source Server. The mapping of the Gene Ontology, with its focus on structures, processes and functions at the molecular level, to the existing broad coverage UMLS should contribute to linking the language and practices of clinical medicine to the language and practices of genomics.

Personalised health document summarisation exploiting Unified Medical Language System and topic-based clustering for mobile healthcare

2017 ◽  
Vol 44 (5) ◽  
pp. 619-643 ◽  
Author(s):  
Gun-Woo Kim ◽  
Dong-Ho Lee
Keyword(s):  
Mobile Devices ◽  
Information Overload ◽  
Personal Health Record ◽  
Personal Health ◽  
Medical Terminology ◽  
Language System ◽  
Unified Medical Language System ◽  
Mobile Healthcare ◽  
Medical Language ◽  
Semantic Types

According to the growing interest in mobile healthcare, multi-document summarisation techniques are increasingly required to cope with health information overload and effectively deliver personalised online healthcare information. However, because of the peculiarities of medical terminology and the diversity of subtopics in health documents, multi-document summarisation must consider technical aspects that are different from those of the general domain. In this article, we propose a personalised health document summarisation system that provides a reliable personal health-related summary to general healthcare consumers via mobile devices. Our system generates a personalised summary from multiple online health documents by exploiting biomedical concepts, semantic types and semantic relations extracted from the Unified Medical Language System (UMLS) and analysing individual health records derived from mobile personal health record (PHR) applications. Furthermore, to increase the diversity and coverage of summarised results and to display them in a user-friendly manner on mobile devices, we create a summary that is categorised into subtopics by grouping semantically related sentences through topic-based clustering. The experimental evaluations demonstrate the effectiveness of our proposed system.

scholarly journals A chemical specialty semantic network for the Unified Medical Language System

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
C Paul Morrey ◽  
Yehoshua Perl ◽  
Michael Halper ◽  
Ling Chen ◽  
Huanying “Helen” Gu
Keyword(s):  
Semantic Network ◽  
Language System ◽  
Unified Medical Language System ◽  
Medical Language

scholarly journals A Silver Standard Biomedical Corpus for Arabic Language

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Nada Boudjellal ◽  
Huaping Zhang ◽  
Asif Khan ◽  
Arshad Ahmad ◽  
Rashid Naseem ◽  
...  
Keyword(s):  
Information Extraction ◽  
English Language ◽  
Arabic Language ◽  
Biomedical Domain ◽  
Language System ◽  
Unified Medical Language System ◽  
Silver Standard ◽  
Medical Language ◽  
System Concept ◽  
Short Time

The rapidly growing data in many areas, as well as in the biomedical domain, require the assistance of information extraction systems to acquire the much needed knowledge about specific entities such as proteins, drugs, or diseases practically within a short time. Annotated corpora serve the purpose of facilitating the process of building NLP systems. While colossal work has been done in this area for English language, other languages like Arabic seem to lack these resources, especially in the healthcare area. Therefore, in this work, we present a method to develop a silver standard medical corpus for the Arabic language with a dictionary as a minimal supervision tool. The corpus contains 49,856 sentences tagged with 13 entity types corresponding to a subset of UMLS (Unified Medical Language System) concept types. The evaluation of a subset of corpus showed the efficiency of the method used to annotate it with 90% accuracy.

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