Umls-based analysis of medical terminology coverage for tags in diabetes-related blogs

There is a well-known terminology disparity between laypeople and health professionals. Using the Unified Medical Language System (UMLS), this study explores an exploratory study on the terminology usages of laypeople, focusing on diabetes. We explain the analysis pipeline of extracting laypeople’s medical terms and matching them to the existing medical controlled vocabulary system. The preliminary result shows the promise of using the UMLS and Tumblr data for such analysis

HealthTranslator: automatic annotation of Web documents in order to assist health consumer's searches

A Web é agora uma das principais fontes de informação relativa a saúde. No entanto, consumidores de saúde nem sempre compreendem facilmente a informação obtida, principalmente devido a uma discrepância significante nas terminologias usadas por leigos e especialistas de saúde. Este trabalho apresenta uma ferramenta, disponível como uma extensão para o Google Chrome, que ajuda os utilizadores a ultrapassar as dificuldades com que se deparam ao ler documentos na Web relacionados com saúde. Esta efetua uma anotação automática de conceitos médicos em documentos Web com apresentação de informação adicional ao utilizador, como definição do conceito, relações com conceitos semelhantes ou ligação a recursos externos. As linguagens portuguesa e inglesa serão suportadas. De forma a avaliar a solução desenvolvida, a sua anotação será comparada com um corpus português e inglês. Enquanto o primeiro será manualmente anotado, o último é uma anotação automática efetuada por uma extensão semelhante, designada Medical Translator. Também será feito um estudo de utilizador, de forma a perceber a sua opinião e avaliar a utilidade da ferramenta. É também apresentado o planeamento para a dissertação, de modo a atingir os objetivos definidos.The Web is now one of the main sources of health related information. However, health consumers do not always easily understand the retrieved information, mainly because of a significant gap between terminologies used by laypeople and medical experts. This work presents a tool, available as Google Chrome extension, that helps users to overcome the difficulties they face when reading health Web documents. It provides automatic annotation of medical concepts in Web documents with additional information, such as concept definition, relationships with related concepts or linkage to external resources. Both Portuguese and English languages will be supported. In order to evaluate the developed solution, its' annotation will be compared with Portuguese and an English corpus. While the first one will be manually annotated, the latter is an automatic annotation performed by a similar extension, named Medical Translator. A user study will also be conducted, in order to understand their opinion and evaluate the tool utility. It is also presented the planning for the dissertation, in order to achieve the defined goals

Personalized patient education and the internet : Linking health information to the Electronic Patient Record : STEPPS in burn care

Väitöskirja, sis. artikkelitSTEPPS = STructured Evaluated Personalized Patient Support = Rakenteinen, arvioitu ja yksilöllistetty potilastuk

The development of a reference database of health information resources to facilitate informed lifestyle choice

This study investigates, within the current health care situation, the interrelationship of the user, resources and tool in the design of a prototype WELLNESS database-driven web site. A shift has taken place in health care, in which the base of conventional medicine has broadened to integrate other systems, practices and worldviews. These include complementary and alternative medicine, health promotion, disease prevention and wellness. Emphasis is placed on the need to take personal responsibility for one's own health and wellness. The global burden of chronic disease, reaching epidemic proportions, is increasingly linked to risk factors resulting from personal lifestyle choices. The growing evidence of the user's need to make personal, informed, lifestyle choices and their reliance on the Web for health information, required investigation. WELLNESS, a specific orientation to health and wellness, formed the framework within which the user and resources were defined and the tool designed. The user was profiled as the WELLNESS health information seeker, hereby contributing significantly to an understanding of the user in this new context. The user profile informed the establishment of resource selection criteria and tool design. The identification of WELLNESS content selection criteria, within a five-dimensional model, was required to ensure quality, relevant and credible resources. The tool is comprised of the WELLNESS thesaurus and WELLNESS database-driven web site. The WELLNESS thesaurus was constructed based on a combination of relevant thesauri. It will be used as an indexing tool. An investigation of existing health information web sites highlighted the importance of designing a specific WELLNESS database-driven web site. A database host was identified against which the original study's conceptual schema was assessed. A low-fidelity prototype web site was designed as the interface between the WELLNESS health information seeker and the database of WELLNESS health information resources. This study has epidemiological, philosophical, epistemological, sociological and psychological relevance. The provision of access to WELLNESS health information resources, made available in the WELLNESS database-driven web site, for personal, informed lifestyle choice by the WELLNESS health information seeker could potentially contribute to the reduction of the global burden of chronic disease.Information ScienceD.Litt. et Phil. (Information Science

Mining document, concept, and term associations for effective biomedical retrieval - Introducing MeSH-enhanced retrieval models

Manually assigned subject terms, such as Medical Subject Headings (MeSH) in the health domain, describe the concepts or topics of a document. Existing information retrieval models do not take full advantage of such information. In this paper, we propose two MeSH-enhanced (ME) retrieval models that integrate the concept layer (i.e. MeSH) into the language modeling framework to improve retrieval performance. The new models quantify associations between documents and their assigned concepts to construct conceptual representations for the documents, and mine associations between concepts and terms to construct generative concept models. The two ME models reconstruct two essential estimation processes of the relevance model (Lavrenko and Croft 2001) by incorporating the document-concept and the concept-term associations. More specifically, in Model 1, language models of the pseudo-feedback documents are enriched by their assigned concepts. In Model 2, concepts that are related to users’ queries are first identified, and then used to reweight the pseudo-feedback documents according to the document-concept associations. Experiments carried out on two standard test collections show that the ME models outperformed the query likelihood model, the relevance model (RM3), and an earlier ME model. A detailed case analysis provides insight into how and why the new models improve/worsen retrieval performance. Implications and limitations of the study are discussed. This study provides new ways to formally incorporate semantic annotations, such as subject terms, into retrieval models. The findings of this study suggest that integrating the concept layer into retrieval models can further improve the performance over the current state-of-the-art models.Ye

Doctor of Philosophy

dissertationThe problem of information transfer between healthcare sectors and across the continuum of care was examined using a mixed methods approach. These methods include qualitative interviews, retrospective case reviews and an informatic gap analysis. Findings and conclusions are reported for each study. Qualitative interviews were conducted with 16 healthcare representatives from 4 disciplines (medicine, pharmacy, nursing, and social work) and 3 healthcare sectors (hospital, skilled nursing care and community care). Three key themes from a Joint Cognitive Systems theoretical model were used to examine qualitative findings. Agreement on cross-sector care goals is neither defined nor made explicit and in some instances working at cross purposes. Care goals and information paradigms change as patients move from hospitalbased crisis stabilization, diagnosis and treatment to a postdischarge care to home or skilled nursing recovery, function restoration, or end of life support. Control of the transfer process is variable across institutions with little feedback and feed-forward. Lack of knowledge, competency and information tracking threatens sector interdependencies with suspicion and distrust. Sixty-three patients discharged between 2006 and 2008 from hospitals to skilled nursing facilities were randomly selected and reviewed. Most notably missing are discharge summaries (30%), nursing assessments or notes (17%), and social work documents (25%). Advanced directives or living wills necessary for end of life support were present in only 6% of the cases. The presence of information on activities of daily living (ADLs), other disabling conditions, and nutrition was associated with positive outcomes at the 0.001, 0.04 and 0.08levels. Consistent geriatric information transfer across the continuum is needed for relevant care management. An interoperability gap analysis conducted on the LINC (Linking Information Necessary for Care) transfer form determined its interoperability to be the semantic level 0. Detailed Clinical Models representing care management processes are challenged by the lack of consensus in terminology standards across sectors. Construction of information transfer solutions compliant with the Centers of Medicare and Medicaid Services (CMS) Stage 2 meaningful use criteria must address syntactic and semantic standards, map sector terminologies within care management processes, and account for the lack of standard terminologies in allied health domains

Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of Semantic Web

UNIVERSITY OF LIÈGE, BELGIUM Executive Summary Faculty of Medicine Département Universitaire de Médecine Générale. Unité de recherche Soins Primaires et Santé Doctor in biomedical sciences Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of SemanticWeb by Dr. Marc JAMOULLE Introduction This thesis is about giving visibility to the often overlooked work of family physicians and consequently, is about grey literature in General Practice and Family Medicine (GP/FM). It often seems that conference organizers do not think of GP/FM as a knowledge-producing discipline that deserves active dissemination. A conference is organized, but not much is done with the knowledge shared at these meetings. In turn, the knowledge cannot be reused or reapplied. This these is also about indexing. To find knowledge back, indexing is mandatory. We must prepare tools that will automatically index the thousands of abstracts that family doctors produce each year in various languages. And finally this work is about semantics1. It is an introduction to health terminologies, ontologies, semantic data, and linked open data. All are expressions of the next step: Semantic Web for health care data. Concepts, units of thought expressed by terms, will be our target and must have the ability to be expressed in multiple languages. In turn, three areas of knowledge are at stake in this study: (i) Family Medicine as a pillar of primary health care, (ii) computational linguistics, and (iii) health information systems. Aim • To identify knowledge produced by General practitioners (GPs) by improving annotation of grey literature in Primary Health Care • To propose an experimental indexing system, acting as draft for a standardized table of content of GP/GM • To improve the searchability of repositories for grey literature in GP/GM. 1For specific terms, see the Glossary page 257 x Methods The first step aimed to design the taxonomy by identifying relevant concepts in a compiled corpus of GP/FM texts. We have studied the concepts identified in nearly two thousand communications of GPs during conferences. The relevant concepts belong to the fields that are focusing on GP/FM activities (e.g. teaching, ethics, management or environmental hazard issues). The second step was the development of an on-line, multilingual, terminological resource for each category of the resulting taxonomy, named Q-Codes. We have designed this terminology in the form of a lightweight ontology, accessible on-line for readers and ready for use by computers of the semantic web. It is also fit for the Linked Open Data universe. Results We propose 182 Q-Codes in an on-line multilingual database (10 languages) (www.hetop.eu/Q) acting each as a filter for Medline. Q-Codes are also available under the form of Unique Resource Identifiers (URIs) and are exportable in Web Ontology Language (OWL). The International Classification of Primary Care (ICPC) is linked to Q-Codes in order to form the Core Content Classification in General Practice/Family Medicine (3CGP). So far, 3CGP is in use by humans in pedagogy, in bibliographic studies, in indexing congresses, master theses and other forms of grey literature in GP/FM. Use by computers is experimented in automatic classifiers, annotators and natural language processing. Discussion To the best of our knowledge, this is the first attempt to expand the ICPC coding system with an extension for family physician contextual issues, thus covering non-clinical content of practice. It remains to be proven that our proposed terminology will help in dealing with more complex systems, such as MeSH, to support information storage and retrieval activities. However, this exercise is proposed as a first step in the creation of an ontology of GP/FM and as an opening to the complex world of Semantic Web technologies. Conclusion We expect that the creation of this terminological resource for indexing abstracts and for facilitating Medline searches for general practitioners, researchers and students in medicine will reduce loss of knowledge in the domain of GP/FM. In addition, through better indexing of the grey literature (congress abstracts, master’s and doctoral theses), we hope to enhance the accessibility of research results and give visibility to the invisible work of family physicians

Semi-automated Ontology Generation for Biocuration and Semantic Search

Background: In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed. Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing. Motivation: The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences. Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods. Results: The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results. To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org