Alexa T. McCray

Exploring semantic groups through visual approaches

Objectives. We investigate several visual approaches for exploring semantic groups, a grouping of semantic types from the Unified Medical Language System (UMLS) semantic network. We are particularly interested in the semantic coherence of the groups, and we use the semantic relationships as important indicators of that coherence. Methods. First, we create a radial representation of the number of relationships among the groups, generating a profile for each semantic group. Second, we show that, in our partition, the relationships are organized around a limited number of pivot groups and that partitions created at random do not exhibit this property. Finally, we use correspondence analysis to visualize groupings resulting from the association between semantic types and the relationships. Results. The three approaches provide different views on the semantic groups and help detect potential inconsistencies. They make outliers immediately apparent, and, thus, serve as a tool for auditing and validating both the semantic network and the semantic groups.

An upper‐level ontology for the biomedical domain

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 NLMs 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.

Evaluating the Coverage of Controlled Health Data Terminologies: Report on the Results of the NLM/AHCPR Large Scale Vocabulary Test

OBJECTIVE To determine the extent to which a combination of existing machine-readable health terminologies cover the concepts and terms needed for a comprehensive controlled vocabulary for health information systems by carrying out a distributed national experiment using the Internet and the UMLS Knowledge Sources, lexical programs, and server. METHODS Using a specially designed Web-based interface to the UMLS Knowledge Source Server, participants searched the more than 30 vocabularies in the 1996 UMLS Metathesaurus and three planned additions to determine if concepts for which they desired controlled terminology were present or absent. For each term submitted, the interface presented a candidate exact match or a set of potential approximate matches from which the participant selected the most closely related concept. The interface captured a profile of the terms submitted by the participant and for each term searched, information about the concept (if any) selected by the participant. The term information was loaded into a database at NLM for review and analysis and was also available to be downloaded by the participant. A team of subject experts reviewed records to identify matches missed by participants and to correct any obvious errors in relationships. The editors of SNOMED International and the Read Codes were given a random sample of reviewed terms for which exact meaning matches were not found to identify exact matches that were missed or any valid combinations of concepts that were synonymous to input terms. The 1997 UMLS Metathesaurus was used in the semantic type and vocabulary source analysis because it included most of the three planned additions. RESULTS Sixty-three participants submitted a total of 41,127 terms, which represented 32,679 normalized strings. More than 80% of the terms submitted were wanted for parts of the patient record related to the patients condition. Following review, 58% of all submitted terms had exact meaning matches in the controlled vocabularies in the test, 41% had related concepts, and 1% were not found. Of the 28% of the terms which were narrower in meaning than a concept in the controlled vocabularies, 86% shared lexical items with the broader concept, but had additional modification. The percentage of exact meanings matches varied by specialty from 45% to 71%. Twenty-nine different vocabularies contained meanings for some of the 23,837 terms (a maximum of 12,707 discrete concepts) with exact meaning matches. Based on preliminary data and analysis, individual vocabularies contained < 1% to 63% of the terms and < 1% to 54% of the concepts. Only SNOMED International and the Read Codes had more than 60% of the terms and more than 50% of the concepts. CONCLUSIONS The combination of existing controlled vocabularies included in the test represents the meanings of the majority of the terminology needed to record patient conditions, providing substantially more exact matches than any individual vocabulary in the set. From a technical and organizational perspective, the test was successful and should serve as a useful model, both for distributed input to the enhancement of controlled vocabularies and for other kinds of collaborative informatics research.

Principles for digital library development

COMMUNICATIONS OF THE ACM May 2001/Vol. 44, No. 5 49 Adhering to the following set of 10 principles (see Figure 1), as well as to the practices that evolve from them, benefits those responsible for the design and continued development of any digital library system, and, perhaps, more important, continues to pay off over the long-term. The principles are derived from our experience developing digital library systems over the past decade [7]. We migrated one digital library (created in the early 1990s, before any thought of serving its contents over the Internet) into a more recently created system called Profiles in Science (profiles.nlm.nih.gov/). Even though the original hardware and software in the two systems were completely different, the migration was successful, because each was designed with the same basic principles in mind. Expect change. It may not be apparent why the changing technology landscape is such a thorny problem for digital library projects. Consider, for example, a conversion project in which documents are converted to some digital format. If the chosen format is part of a proprietary system, viewable only through a proprietary interface, when the company that markets the interface no longer supports the system and format, the digitized documents are all but lost. Consider, too, a scenario in which a document is created in a particular word processing program and the document is attached to an email message sent to a notable person. Suppose the goal is to preserve all of that person’s email messages for future generations. We are all too aware of our dependence on our email technology for reading such attachments. Imagine what today’s platform limitations will mean to future generations, when the content Alexa T. McCray and Marie E. Gallagher { {

Data analysis and data mining: current issues in biomedical informatics.

BACKGROUND Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. OBJECTIVES To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. METHODS On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. RESULTS The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. CONCLUSIONS Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.

Extending the role of metadata in a digital library system

We describe an approach to the development of a digital library system that is founded on a number of basic principles. In particular, we discuss the critical role of metadata in all aspects of the system design. We begin by describing how the notion of metadata is sometimes interpreted and go on to discuss some of our early experiences in a digital conversion project. We report on the Profiles in Science project, which is making the archival collections of prominent biomedical scientists available on the World Wide Web. We discuss the principles that are used in our system design, illustrating these throughout the discussion. Our approach has involved interpreting metadata in its broadest sense. We capture data about the items in our digital collection for a a variety of purposes and use those data to drive the entire system. Further, we have designed our overall system architecture such that it can accommodate changes while still ensuring the persistence of the underlying data.

Mapping the Gene Ontology Into the Unified Medical Language System

We have recently mapped the Gene Ontology (GO), developed by the Gene Ontology Consortium, into the National Library of Medicines 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.

A Conceptual Framework for the Biomedical Domain

Specialized domains often come with an extensive terminology, suitable for storing and exchanging information, but not necessarily for knowledge processing. Knowledge structures such as semantic networks, or ontologies, are required to explore the semantics of a domain. The UMLS project at the National Library of Medicine is a research effort to develop knowledge-based resources for the biomedical domain. The Metathesaurus is a large body of knowledge that defines and inter-relates 730,000 biomedical concepts, and the Semantic Network defines the semantic principles that apply to this domain. This chapter presents these two knowledge sources and illustrates through a research study how they can collaborate to further structure the domain. The limits of the approach are discussed.

Undiagnosed Diseases Network International (UDNI): White paper for global actions to meet patient needs

In 2008, the National Institutes of Healths (NIH) Undiagnosed Disease Program (UDP) was initiated to provide diagnoses for individuals who had long sought one without success. As a result of two international conferences (Rome 2014 and Budapest 2015), the Undiagnosed Diseases Network International (UDNI) was established, modeled in part after the NIH UDP. Undiagnosed diseases are a global health issue, calling for an international scientific and healthcare effort. To meet this demand, the UDNI has built a consensus framework of principles, best practices and governance; the Board of Directors reflects its international character, as it includes experts from Australia, Canada, Hungary, Italy, Japan and the USA. The UDNI involves centers with internationally recognized expertise, and its scientific resources and know-how aim to fill the knowledge gaps that impede diagnosis. Consequently, the UDNI fosters the translation of research into medical practice. Active patient involvement is critical; the Patient Advisory Group is expected to play an increasing role in UDNI activities. All information for physicians and patients will be available at the UDNI website.

Making the Conceptual Connections: The UMLS after a Decade of Research and Development

The UMLS Section in this issue of JAMIA is dedicated to the memory of Marsden Scott Blois, Jr., a pioneer in medical concept representation. Dr. Blois, an internationally recognized physician-investigator and medical informatician, made important contributions to melanoma research and to biomedical informatics during his distinguished and varied career. His keen insight in the early days of the UMLS project contributed significantly to the future direction and success of the project. This issue of JAMIA helps mark the tenth anniversary of the Unified Medical Language System (UMLS) project. From the beginning, the project has focused on overcoming the barriers users face when attempting to interact with computerized health information systems. The UMLS developers and their collaborators envisioned and then created a set of knowledge sources designed to support the development of sophisticated and accessible information systems. The UMLS knowledge sources have grown to …