Turning Text into Research Networks: Information Retrieval and Computational Ontologies in the Creation of Scientific Databases

BACKGROUND: Web-based, free-text documents on science and technology have been increasing growing on the web. However, most of these documents are not immediately processable by computers slowing down the acquisition of useful information. Computational ontologies might represent a possible solution by enabling semantically machine readable data sets. But, the process of ontology creation, instantiation and maintenance is still based on manual methodologies and thus time and cost intensive. METHOD: We focused on a large corpus containing information on researchers, research fields, and institutions. We based our strategy on traditional entity recognition, social computing and correlation. We devised a semi automatic approach for the recognition, correlation and extraction of named entities and relations from textual documents which are then used to create, instantiate, and maintain an ontology. RESULTS: We present a prototype demonstrating the applicability of the proposed strategy, along with a case study describing how direct and indirect relations can be extracted from academic and professional activities registered in a database of curriculum vitae in free-text format. We present evidence that this system can identify entities to assist in the process of knowledge extraction and representation to support ontology maintenance. We also demonstrate the extraction of relationships among ontology classes and their instances. CONCLUSION: We have demonstrated that our system can be used for the conversion of research information in free text format into database with a semantic structure. Future studies should test this system using the growing number of free-text information available at the institutional and national levels

A presença da metáfora em artigos de investigação biomédica

O projecto “O Uso de Metáforas na Pesquisa Biomédica” tem como objectivo geral compreender como a utilização das metáforas pode influenciar a pesquisa biomédica e prevê a inclusão de uma revisão da literatura recentemente publicada sobre o assunto, tanto em formato livro como em artigos de investigação. Nesta comunicação, apresentamos os resultados da revisão dos artigos de investigação com origem em áreas biomédicas e conexas recentemente publicados e acessíveis através da base de dados online da PubMed®. Através do respectivo sítio na Internet, foram compilados 319 artigos com data de publicação entre Janeiro de 2010 e Setembro de 2012, mencionando o termo “metaphor” no título ou resumo. Depois de enquadrados num panorama cronológico mais amplo, estes artigos foram caracterizados segundo a respectiva tipologia e identificadas as áreas disciplinares de maior interesse pelo tema. Seguidamente, foram analisados o modo como a influência da metáfora neles é percebida pelos próprios investigadores e as interpretações mais comuns do termo, revelando quais serão as suas acepções mais correntes entre um público de formação superior, mas presumivelmente alheio aos aspectos técnicos dos debates que se têm desenvolvido acerca da metáfora na área da filosofia. Finalmente, procurámos distinguir nos artigos compilados as linhas de investigação mais relevantes sobre a metáfora na área da biomedicina.The overall objective of the project “The use of metaphors in biomedical research” is to understand some of the ways by which the use of metaphor may influence biomedical research and includes a survey of the most recently published literature on the subject, in books as well as in research papers. This paper presents the results of a survey of research articles in biomedical areas that have been recently published and are accessible through PubMed®, an online database. Through its internet site, 319 research articles have been compiled, with publishing dates ranging from January 2010 to September 2012. All of these articles hold the word “metaphor” in their title and / or their abstract. These articles were then included within a wider chronological frame. They were then divided by different categories according to the disciplinary areas that are more keen on the subject. Subsequently, we were able to identify the way the use of metaphor is acknowledged and understood by researchers themselves and what are the most common interpretations of this notion amidst the scientific community. Finally we were able to identify what are the most relevant areas of research on metaphor within biomedical studies.info:eu-repo/semantics/publishedVersio

Metáforas na investigação biomédica: diagnóstico e tipologia

A presente comunicação apresenta os primeiros resultados da análise de um conjunto de artigos publicados na área da pesquisa biomédica no que respeita à utilização da metáfora. O objectivo aqui é indicar como, a partir de uma abordagem cognitivista, elaborámos uma extensa listagem de conceitos metafóricos posteriormente classificados e ordenados num elenco de oito grandes categorias. Finalmente, apontamos o modo como estas categorias poderão servir de base a uma análise mais detalhada no que respeita aos processos de nomeação dos conceitos usados na área da biomedicina, à elaboração de uma ontologia da representação que, de certa forma, modela e condiciona a actividade dos investigadores, ao desenvolvimento de uma possível distinção entre metáforas “comuns”, metáforas “epistémicas” e metáforas “disciplinares”, e ainda quanto à caracterização do uso da metáfora em alguns fenómenos de tipo pragmático.info:eu-repo/semantics/publishedVersio

Dez anos de crescimento da produção científica da Psiquiatria brasileira: o impacto das novas políticas de avaliação

OBJECTIVE: Developed by the Ministry of Education, the Qualis evaluation criteria have strongly impacted the scientific production of Post-Graduation Programs. A new set of more stringent criteria has been proposed for Qualis. Our aim was to evaluate the impact of the new Qualis criteria on the scientific production of Post-Graduation Programs in psychiatry over the last 10 years. METHOD:We extracted data from annual reports published between 1998 and 2008, and compared performance measured in terms of the old Qualis rating criteria and the new set of criteria. RESULTS: There was a 25% increase in the number of Information Science Institute-indexed articles in the second five-year period, which rose from 1,213 to 1,518. While, according to the old Qualis criteria, 84% of the Information Science Institute production would have been classified as highly-rated (IF > 1), only 17% of the papers were classified as highly-rated (A1) according to the new Qualis rating criteria. Most papers (65%) were assigned to intermediate categories (B1 and B2) with an IF 1), apenas 17% dos trabalhos foram classificados como de alta qualificação (A1), de acordo com os novos critérios de avaliação Qualis. A maioria dos trabalhos (65%) foi atribuída a categorias intermediárias (B1 e B2), com IF < 2,29. DISCUSSÃO:Todos os Programas de Pós-Graduação de psiquiatria aumentaram sua produção, porém, favorecendo a qualidade ao invés da quantidade, as novas regras provaram ser de mais utilidade para discriminar a produção científica.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo (UNIFESP)Instituto Israelita de Ensino e Pesquisa Albert EinsteinDuke University Health SystemKing's College London Institute of PsychiatryUNIFESPSciEL

High Hospital Volume Is Associated with Better Outcomes for Breast Cancer Surgery: Analysis of 233,247 Patients

Background:: The relationship between hospital volume and outcomes needs to be further elucidated for low-risk procedures such as surgical therapy of localized breast cancer. The objective of this investigation was to assess the relationship between hospital volume and outcomes for breast cancer surgery. Methods:: A total of 233,247 patients who underwent breast-conserving therapy (BCT) and breast-ablative therapy (BAT) for localized breast cancer were extracted from 13 years (1988-2000) of the Nationwide Inpatient Samples. Hospital volume was classified as low (<30 cases/year), intermediate (≥ 30 to <70cases/year), and high (≥ 70 cases/year). Multiple linear and logistic regression analyses were used to assess the risk-adjusted association between hospital volume and outcomes. Results:: In risk-adjusted analyses, patients operated on at low-volume hospitals were 3.04 (p = 0.03) times more likely to die after BCT compared with patients operated on at high-volume hospitals. Similarly, low-volume hospitals had a significantly higher likelihood of postoperative complications (odds ratio [OR] = 1.73, p = 0.01 for BCT; OR = 1.44, p < 0.001 for BAT) compared with high-volume hospitals. Compared with low-volume hospitals, length of hospital stay was significantly shorter and nonroutine patient discharge significantly lower for high-volume providers for both BCT and BAT (all p < 0.001). Patients were also significantly less likely to undergo BCT if operated on in a low- or intermediate-volume hospital compared with a high-volume provider (p < 0.001). Conclusions:: High-volume hospitals had significantly lower nonroutine patient discharge, postoperative morbidity and mortality, shorter length of hospital stay, and higher likelihood of performing BCT. Referral of patients with localized breast cancer to high-volume hospitals may be justifie

VisualDecisionLinc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry

Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients

Predicting gender differences as latent variables: summed scores, and individual item responses: a methods case study

BACKGROUND: Modeling latent variables such as physical disability is challenging since its measurement is performed through proxies. This poses significant methodological challenges. The objective of this article is to present three different methods to predict latent variables based on classical summed scores, individual item responses, and latent variable models. METHODS: This is a review of the literature and data analysis using "layers of information". Data was collected from the North Carolina Back Pain Project, using a modified version of the Roland Questionnaire. RESULTS: The three models are compared in relation to their goals and underlying concepts, previous clinical applications, data requirements, statistical theory, and practical applications. Initial linear regression models demonstrated a difference in disability between genders of 1.32 points (95% CI 0.65, 2.00) on a scale from 0–23. Subsequent item analysis found contradictory results across items, with no clear pattern. Finally, IRT models demonstrated three items were demonstrated to present differential item functioning. After these items were removed, the difference between genders was reduced to 0.78 points (95% CI, -0.99, 1.23). These results were shown to be robust with re-sampling methods. CONCLUSIONS: Purported differences in the levels of a latent variable should be tested using different models to verify whether these differences are real or simply distorted by model assumptions

Qualitative Analysis of the Interdisciplinary Interaction between Data Analysis Specialists and Novice Clinical Researchers

Background: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. Methods/Principal Findings: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of ""what if'' situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. Conclusion/Significance: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors