881 resultados para text searching
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Purpose - There are many library automation packages available as open-source software, comprising two modules: staff-client module and online public access catalogue (OPAC). Although the OPAC of these library automation packages provides advanced features of searching and retrieval of bibliographic records, none of them facilitate full-text searching. Most of the available open-source digital library software facilitates indexing and searching of full-text documents in different formats. This paper makes an effort to enable full-text search features in the widely used open-source library automation package Koha, by integrating it with two open-source digital library software packages, Greenstone Digital Library Software (GSDL) and Fedora Generic Search Service (FGSS), independently. Design/methodology/approach - The implementation is done by making use of the Search and Retrieval by URL (SRU) feature available in Koha, GSDL and FGSS. The full-text documents are indexed both in Koha and GSDL and FGSS. Findings - Full-text searching capability in Koha is achieved by integrating either GSDL or FGSS into Koha and by passing an SRU request to GSDL or FGSS from Koha. The full-text documents are indexed both in the library automation package (Koha) and digital library software (GSDL, FGSS) Originality/value - This is the first implementation enabling the full-text search feature in a library automation software by integrating it into digital library software.
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Background: Work-related injuries in Australia are estimated to cost around $57.5 billion annually, however there are currently insufficient surveillance data available to support an evidence-based public health response. Emergency departments (ED) in Australia are a potential source of information on work-related injuries though most ED’s do not have an ‘Activity Code’ to identify work-related cases with information about the presenting problem recorded in a short free text field. This study compared methods for interrogating text fields for identifying work-related injuries presenting at emergency departments to inform approaches to surveillance of work-related injury.---------- Methods: Three approaches were used to interrogate an injury description text field to classify cases as work-related: keyword search, index search, and content analytic text mining. Sensitivity and specificity were examined by comparing cases flagged by each approach to cases coded with an Activity code during triage. Methods to improve the sensitivity and/or specificity of each approach were explored by adjusting the classification techniques within each broad approach.---------- Results: The basic keyword search detected 58% of cases (Specificity 0.99), an index search detected 62% of cases (Specificity 0.87), and the content analytic text mining (using adjusted probabilities) approach detected 77% of cases (Specificity 0.95).---------- Conclusions The findings of this study provide strong support for continued development of text searching methods to obtain information from routine emergency department data, to improve the capacity for comprehensive injury surveillance.
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- Objective To explore the potential for using a basic text search of routine emergency department data to identify product-related injury in infants and to compare the patterns from routine ED data and specialised injury surveillance data. - Methods Data was sourced from the Emergency Department Information System (EDIS) and the Queensland Injury Surveillance Unit (QISU) for all injured infants between 2009 and 2011. A basic text search was developed to identify the top five infant products in QISU. Sensitivity, specificity, and positive predictive value were calculated and a refined search was used with EDIS. Results were manually reviewed to assess validity. Descriptive analysis was conducted to examine patterns between datasets. - Results The basic text search for all products showed high sensitivity and specificity, and most searches showed high positive predictive value. EDIS patterns were similar to QISU patterns with strikingly similar month-of-age injury peaks, admission proportions and types of injuries. - Conclusions This study demonstrated a capacity to identify a sample of valid cases of product-related injuries for specified products using simple text searching of routine ED data. - Implications As the capacity for large datasets grows and the capability to reliably mine text improves, opportunities for expanded sources of injury surveillance data increase. This will ultimately assist stakeholders such as consumer product safety regulators and child safety advocates to appropriately target prevention initiatives.
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Search strategy and free text searching of database resources for Health Sciences
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Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations. Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging. This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching. In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays. Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.
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Objective: Our objective was to systematically review the published observational research related to the role of oxidative-nitrosative stress in pathogenesis of dengue. Methods: We searched electronic databases (PubMed, EMBASE, The COCHRANE library, ScienceDirect, Scopus, SciELO, LILACS via Virtual Health Library, Google Scholar) using the term: dengue, dengue virus, severe dengue, oxidative stress, nitrosative stress, antioxidants, oxidants, free radicals, oxidized lipid products, lipid peroxides, nitric oxide, and nitric oxide synthase. Articles were selected for review by title and abstract excluding letter, review, in vivo and in vitro studies, and duplicates studies. Selected articles were reviewed for study design, original purposes, sample size, main outcomes, methods, and oxidative-nitrosative stress markers values. Results: In total, 4,331 non-duplicates articles were identified from electronic databases searches, of which 16 were eligible for full text searching. Data from the observational studies originate from Asian countries (50%; 8/16), South American countries (31.2%; 5/16), and Central America and the Caribbean countries (18.8%; 3/16). Casecontrol study was the type of design most common in researches reviewed. The 1997 World Health Organization (WHO) dengue case classification criteria were used in all studies included in this review. Conclusions: Based on published data found in peer-reviewed literature, oxidative and nitrosative stress are demonstrated by changes in plasma levels of nitric oxide, antioxidants, lipid peroxidation and protein oxidation markers in patients with dengue infection. Additionally, elevated serum protein carbonyls and malondialdehyde levels appear to be associated with dengue disease severity.
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Objetivo: Identificar factores sociodemográficos y de fecundidad, asociados a ocurrencia de embarazo no deseado en mujeres colombianas en edad reproductiva en el año 2010. Métodos: Se realizó estudio retrospectivo de corte transversal, basado en los datos de la ENDS Colombia-2010, del total de mujeres en edad fértil (13-49 años) que al momento de la encuesta se encontraban en embarazo. La variable de interés fue embarazo no deseado, se describió la población a estudio y se evaluó la posible asociación con variables sociodemográficas y de fecundidad, a través de análisis bivariado y multivariado. Se realizaron los mismos análisis por grupo de edad (adolescentes vs adultas). Resultados: La prevalencia de embarazo no deseado en las mujeres colombianas en el 2010 fue de 61,4 %. De acuerdo al modelo de regresión logística, no estar en unión a una pareja (OR: 4,01 IC95%: 3,066-5,269), tener hijos (OR: 2,040 IC95%: 1,581 – 2,631), estar en el quintil de menor riqueza (OR: 2,137 IC95%: 1,328-3,440), y ser adolescente (OR: 1,599 IC95%: 1,183-2,162), son factores que aumentan la probabilidad de tener un embarazo no deseado. Se encontraron diferencias en los factores asociados al realizar segmentación por edad. Conclusiones: La prevalencia de embarazo no deseado permanece alta en Colombia respecto a años anteriores y a otros países. Los resultados pueden ser de utilidad para el desarrollo de políticas en salud sexual y reproductiva teniendo en cuenta los factores asociados identificados priorizando a la población adolescente y de menor estatus socioeconómico, para la prevención de embarazo no deseado en Colombia.
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Introducción: El dolor lumbar y los desórdenes músculo esqueléticos comprometen la salud y la calidad de vida de los trabajadores, pueden poner en riesgo el futuro laboral de las personas. bjetivo: Estimar la prevalencia de dolor lumbar y los posibles factores biomecánicos asociados en el personal operativo y administrativo en una empresa manufacturera de jabón en Bogotá, en el año 2016 Metodología: Estudio de corte transversal donde se evaluó el riesgo biomecánico y la prevalencia del dolor lumbar en personal administrativo (138) y operativo (165); se utilizó como instrumento el ERGOPAR validado en España. Se revisó la asociación utilizando la prueba Chi Cuadrado de Pearson, con un nivel de significación α 0.05 Resultados: 303 trabajadores de una empresa manufacturera de jabón en Bogotá, donde predominó el género masculino (51,82%) y la población adulta media entre 30-39 años (57,42%). La prevalencia del dolor lumbar en la población fue de 61,39% (186). La edad no se asoció estadísticamente al dolor lumbar. Se encontró asociación estadística entre el síntoma dolor lumbar y extensión de cuello (p=0,05 OR1.95 IC 1.33-2.88), así como con agarrar o sujetar objetos (p= 0,036. OR 2.3 IC 1.59-3.51) y con las exigencias físicas laborales (p= 0.001 OR 1.99 IC 1.31-3.02). Conclusiones: La población estudiada presentó una alta prevalencia de dolor lumbar, con predominio en personal que realiza labores operativas, y del género femenino. La adopción de posturas de extensión del cuello y la sujeción o agarre de objetos son factores asociados directamente con la aparición de lumbalgia.
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Vita.
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This work has been partially supported by Grant No. DO 02-275, 16.12.2008, Bulgarian NSF, Ministry of Education and Science.
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Objective: To summarise the extent to which narrative text fields in administrative health data are used to gather information about the event resulting in presentation to a health care provider for treatment of an injury, and to highlight best practise approaches to conducting narrative text interrogation for injury surveillance purposes.----- Design: Systematic review----- Data sources: Electronic databases searched included CINAHL, Google Scholar, Medline, Proquest, PubMed and PubMed Central.. Snowballing strategies were employed by searching the bibliographies of retrieved references to identify relevant associated articles.----- Selection criteria: Papers were selected if the study used a health-related database and if the study objectives were to a) use text field to identify injury cases or use text fields to extract additional information on injury circumstances not available from coded data or b) use text fields to assess accuracy of coded data fields for injury-related cases or c) describe methods/approaches for extracting injury information from text fields.----- Methods: The papers identified through the search were independently screened by two authors for inclusion, resulting in 41 papers selected for review. Due to heterogeneity between studies metaanalysis was not performed.----- Results: The majority of papers reviewed focused on describing injury epidemiology trends using coded data and text fields to supplement coded data (28 papers), with these studies demonstrating the value of text data for providing more specific information beyond what had been coded to enable case selection or provide circumstantial information. Caveats were expressed in terms of the consistency and completeness of recording of text information resulting in underestimates when using these data. Four coding validation papers were reviewed with these studies showing the utility of text data for validating and checking the accuracy of coded data. Seven studies (9 papers) described methods for interrogating injury text fields for systematic extraction of information, with a combination of manual and semi-automated methods used to refine and develop algorithms for extraction and classification of coded data from text. Quality assurance approaches to assessing the robustness of the methods for extracting text data was only discussed in 8 of the epidemiology papers, and 1 of the coding validation papers. All of the text interrogation methodology papers described systematic approaches to ensuring the quality of the approach.----- Conclusions: Manual review and coding approaches, text search methods, and statistical tools have been utilised to extract data from narrative text and translate it into useable, detailed injury event information. These techniques can and have been applied to administrative datasets to identify specific injury types and add value to previously coded injury datasets. Only a few studies thoroughly described the methods which were used for text mining and less than half of the studies which were reviewed used/described quality assurance methods for ensuring the robustness of the approach. New techniques utilising semi-automated computerised approaches and Bayesian/clustering statistical methods offer the potential to further develop and standardise the analysis of narrative text for injury surveillance.
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Information behaviour (IB) is an area within Library and Information Science that studies the totality of human behaviour in relation to information, both active and passive, along with the explicit and the tacit mental states related to information. This study reports on a recently completed dissertation research that integrates the different models of information behaviours using a diary study where 34 participants maintained a daily journal for two weeks through a web log or paper diary. This resulted in thick descriptions of IB, which were manually analysed using the Grounded Theory method of inquiry, and then cross-referenced through both text-analysis and statistical analysis programs. Among the many key findings of this study, one is the focus this paper: how participants express their feelings of the information seeking process and their mental and affective states related specifically to the sense-making component which co-occurs with almost every other aspect of information behaviour. The paper title – Down the Rabbit Hole and Through the Looking Glass – refers to an observation that some of the participants made in their journals when they searched for, or avoided information, and wrote that they felt like they have fallen into a rabbit hole where nothing made sense, and reported both positive feelings of surprise and amazement, and negative feelings of confusion, puzzlement, apprehensiveness, frustration, stress, ambiguity, and fatigue. The study situates this sense-making aspects of IB within an overarching model of information behaviour that includes IB concepts like monitoring information, encountering information, information seeking and searching, flow, multitasking, information grounds, information horizons, and more, and proposes an integrated model of information behaviour illuminating how these different concepts are interleaved and inter-connected with each other, along with it's implications for information services.
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Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.