Search and Graph Database Technologies for Biomedical Semantic Indexing: Experimental Analysis.

PubMed

Segura Bedmar, Isabel; Martínez, Paloma; Carruana Martín, Adrián

2017-12-01

Biomedical semantic indexing is a very useful support tool for human curators in their efforts for indexing and cataloging the biomedical literature. The aim of this study was to describe a system to automatically assign Medical Subject Headings (MeSH) to biomedical articles from MEDLINE. Our approach relies on the assumption that similar documents should be classified by similar MeSH terms. Although previous work has already exploited the document similarity by using a k-nearest neighbors algorithm, we represent documents as document vectors by search engine indexing and then compute the similarity between documents using cosine similarity. Once the most similar documents for a given input document are retrieved, we rank their MeSH terms to choose the most suitable set for the input document. To do this, we define a scoring function that takes into account the frequency of the term into the set of retrieved documents and the similarity between the input document and each retrieved document. In addition, we implement guidelines proposed by human curators to annotate MEDLINE articles; in particular, the heuristic that says if 3 MeSH terms are proposed to classify an article and they share the same ancestor, they should be replaced by this ancestor. The representation of the MeSH thesaurus as a graph database allows us to employ graph search algorithms to quickly and easily capture hierarchical relationships such as the lowest common ancestor between terms. Our experiments show promising results with an F1 of 69% on the test dataset. To the best of our knowledge, this is the first work that combines search and graph database technologies for the task of biomedical semantic indexing. Due to its horizontal scalability, ElasticSearch becomes a real solution to index large collections of documents (such as the bibliographic database MEDLINE). Moreover, the use of graph search algorithms for accessing MeSH information could provide a support tool for cataloging MEDLINE

Essie: A Concept-based Search Engine for Structured Biomedical Text

PubMed Central

Ide, Nicholas C.; Loane, Russell F.; Demner-Fushman, Dina

2007-01-01

This article describes the algorithms implemented in the Essie search engine that is currently serving several Web sites at the National Library of Medicine. Essie is a phrase-based search engine with term and concept query expansion and probabilistic relevancy ranking. Essie’s design is motivated by an observation that query terms are often conceptually related to terms in a document, without actually occurring in the document text. Essie’s performance was evaluated using data and standard evaluation methods from the 2003 and 2006 Text REtrieval Conference (TREC) Genomics track. Essie was the best-performing search engine in the 2003 TREC Genomics track and achieved results comparable to those of the highest-ranking systems on the 2006 TREC Genomics track task. Essie shows that a judicious combination of exploiting document structure, phrase searching, and concept based query expansion is a useful approach for information retrieval in the biomedical domain. PMID:17329729

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources

PubMed Central

Jonquet, Clement; LePendu, Paea; Falconer, Sean; Coulet, Adrien; Noy, Natalya F.; Musen, Mark A.; Shah, Nigam H.

2011-01-01

The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index—a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics “under the hood.” PMID:21918645

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources.

PubMed

Jonquet, Clement; Lependu, Paea; Falconer, Sean; Coulet, Adrien; Noy, Natalya F; Musen, Mark A; Shah, Nigam H

2011-09-01

The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index-a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."

Twitter K-H networks in action: Advancing biomedical literature for drug search.

PubMed

Hamed, Ahmed Abdeen; Wu, Xindong; Erickson, Robert; Fandy, Tamer

2015-08-01

The importance of searching biomedical literature for drug interaction and side-effects is apparent. Current digital libraries (e.g., PubMed) suffer infrequent tagging and metadata annotation updates. Such limitations cause absence of linking literature to new scientific evidence. This demonstrates a great deal of challenges that stand in the way of scientists when searching biomedical repositories. In this paper, we present a network mining approach that provides a bridge for linking and searching drug-related literature. Our contributions here are two fold: (1) an efficient algorithm called HashPairMiner to address the run-time complexity issues demonstrated in its predecessor algorithm: HashnetMiner, and (2) a database of discoveries hosted on the web to facilitate literature search using the results produced by HashPairMiner. Though the K-H network model and the HashPairMiner algorithm are fairly young, their outcome is evidence of the considerable promise they offer to the biomedical science community in general and the drug research community in particular. Copyright © 2015 Elsevier Inc. All rights reserved.

search GenBank: interactive orchestration and ad-hoc choreography of Web services in the exploration of the biomedical resources of the National Center For Biotechnology Information

PubMed Central

2013-01-01

Background Due to the growing number of biomedical entries in data repositories of the National Center for Biotechnology Information (NCBI), it is difficult to collect, manage and process all of these entries in one place by third-party software developers without significant investment in hardware and software infrastructure, its maintenance and administration. Web services allow development of software applications that integrate in one place the functionality and processing logic of distributed software components, without integrating the components themselves and without integrating the resources to which they have access. This is achieved by appropriate orchestration or choreography of available Web services and their shared functions. After the successful application of Web services in the business sector, this technology can now be used to build composite software tools that are oriented towards biomedical data processing. Results We have developed a new tool for efficient and dynamic data exploration in GenBank and other NCBI databases. A dedicated search GenBank system makes use of NCBI Web services and a package of Entrez Programming Utilities (eUtils) in order to provide extended searching capabilities in NCBI data repositories. In search GenBank users can use one of the three exploration paths: simple data searching based on the specified user’s query, advanced data searching based on the specified user’s query, and advanced data exploration with the use of macros. search GenBank orchestrates calls of particular tools available through the NCBI Web service providing requested functionality, while users interactively browse selected records in search GenBank and traverse between NCBI databases using available links. On the other hand, by building macros in the advanced data exploration mode, users create choreographies of eUtils calls, which can lead to the automatic discovery of related data in the specified databases. Conclusions search Gen

search GenBank: interactive orchestration and ad-hoc choreography of Web services in the exploration of the biomedical resources of the National Center For Biotechnology Information.

PubMed

Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Siążnik, Artur

2013-03-01

Due to the growing number of biomedical entries in data repositories of the National Center for Biotechnology Information (NCBI), it is difficult to collect, manage and process all of these entries in one place by third-party software developers without significant investment in hardware and software infrastructure, its maintenance and administration. Web services allow development of software applications that integrate in one place the functionality and processing logic of distributed software components, without integrating the components themselves and without integrating the resources to which they have access. This is achieved by appropriate orchestration or choreography of available Web services and their shared functions. After the successful application of Web services in the business sector, this technology can now be used to build composite software tools that are oriented towards biomedical data processing. We have developed a new tool for efficient and dynamic data exploration in GenBank and other NCBI databases. A dedicated search GenBank system makes use of NCBI Web services and a package of Entrez Programming Utilities (eUtils) in order to provide extended searching capabilities in NCBI data repositories. In search GenBank users can use one of the three exploration paths: simple data searching based on the specified user's query, advanced data searching based on the specified user's query, and advanced data exploration with the use of macros. search GenBank orchestrates calls of particular tools available through the NCBI Web service providing requested functionality, while users interactively browse selected records in search GenBank and traverse between NCBI databases using available links. On the other hand, by building macros in the advanced data exploration mode, users create choreographies of eUtils calls, which can lead to the automatic discovery of related data in the specified databases. search GenBank extends standard capabilities of the

Using a Search Engine-Based Mutually Reinforcing Approach to Assess the Semantic Relatedness of Biomedical Terms

PubMed Central

Hsu, Yi-Yu; Chen, Hung-Yu; Kao, Hung-Yu

2013-01-01

Background Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field. Previous studies, such as those using ontology-based and corpus-based approaches, measured semantic relatedness by using information from the structure of biomedical literature, but these methods are limited by the small size of training resources. To increase the size of training datasets, the outputs of search engines have been used extensively to analyze the lexical patterns of biomedical terms. Methodology/Principal Findings In this work, we propose the Mutually Reinforcing Lexical Pattern Ranking (ReLPR) algorithm for learning and exploring the lexical patterns of synonym pairs in biomedical text. ReLPR employs lexical patterns and their pattern containers to assess the semantic relatedness of biomedical terms. By combining sentence structures and the linking activities between containers and lexical patterns, our algorithm can explore the correlation between two biomedical terms. Conclusions/Significance The average correlation coefficient of the ReLPR algorithm was 0.82 for various datasets. The results of the ReLPR algorithm were significantly superior to those of previous methods. PMID:24348899

search.bioPreprint: a discovery tool for cutting edge, preprint biomedical research articles

PubMed Central

Iwema, Carrie L.; LaDue, John; Zack, Angela; Chattopadhyay, Ansuman

2016-01-01

The time it takes for a completed manuscript to be published traditionally can be extremely lengthy. Article publication delay, which occurs in part due to constraints associated with peer review, can prevent the timely dissemination of critical and actionable data associated with new information on rare diseases or developing health concerns such as Zika virus. Preprint servers are open access online repositories housing preprint research articles that enable authors (1) to make their research immediately and freely available and (2) to receive commentary and peer review prior to journal submission. There is a growing movement of preprint advocates aiming to change the current journal publication and peer review system, proposing that preprints catalyze biomedical discovery, support career advancement, and improve scientific communication. While the number of articles submitted to and hosted by preprint servers are gradually increasing, there has been no simple way to identify biomedical research published in a preprint format, as they are not typically indexed and are only discoverable by directly searching the specific preprint server websites. To address this issue, we created a search engine that quickly compiles preprints from disparate host repositories and provides a one-stop search solution. Additionally, we developed a web application that bolsters the discovery of preprints by enabling each and every word or phrase appearing on any web site to be integrated with articles from preprint servers. This tool, search.bioPreprint, is publicly available at http://www.hsls.pitt.edu/resources/preprint. PMID:27508060

Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search.

PubMed

Ji, Yanqing; Ying, Hao; Tran, John; Dews, Peter; Massanari, R Michael

2016-07-19

Finding highly relevant articles from biomedical databases is challenging not only because it is often difficult to accurately express a user's underlying intention through keywords but also because a keyword-based query normally returns a long list of hits with many citations being unwanted by the user. This paper proposes a novel biomedical literature search system, called BiomedSearch, which supports complex queries and relevance feedback. The system employed association mining techniques to build a k-profile representing a user's relevance feedback. More specifically, we developed a weighted interest measure and an association mining algorithm to find the strength of association between a query and each concept in the article(s) selected by the user as feedback. The top concepts were utilized to form a k-profile used for the next-round search. BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity. A prototype of BiomedSearch software was made and it was preliminarily evaluated using the Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial experiment results indicated that BiomedSearch increased the mean average precision (MAP) for a set of queries. With UMLS and association mining techniques, BiomedSearch can effectively utilize users' relevance feedback to improve the performance of biomedical literature search.

BioEve Search: A Novel Framework to Facilitate Interactive Literature Search

PubMed Central

Ahmed, Syed Toufeeq; Davulcu, Hasan; Tikves, Sukru; Nair, Radhika; Zhao, Zhongming

2012-01-01

Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale of biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of published literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also pave the way to discover hitherto unknown information implicitly conveyed in the texts. Results. We developed a novel framework (named “BioEve”) that seamlessly integrates Faceted Search (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers in life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease. PMID:22693501

The comparative recall of Google Scholar versus PubMed in identical searches for biomedical systematic reviews: a review of searches used in systematic reviews.

PubMed

Bramer, Wichor M; Giustini, Dean; Kramer, Bianca Mr; Anderson, Pf

2013-12-23

The usefulness of Google Scholar (GS) as a bibliographic database for biomedical systematic review (SR) searching is a subject of current interest and debate in research circles. Recent research has suggested GS might even be used alone in SR searching. This assertion is challenged here by testing whether GS can locate all studies included in 21 previously published SRs. Second, it examines the recall of GS, taking into account the maximum number of items that can be viewed, and tests whether more complete searches created by an information specialist will improve recall compared to the searches used in the 21 published SRs. The authors identified 21 biomedical SRs that had used GS and PubMed as information sources and reported their use of identical, reproducible search strategies in both databases. These search strategies were rerun in GS and PubMed, and analyzed as to their coverage and recall. Efforts were made to improve searches that underperformed in each database. GS' overall coverage was higher than PubMed (98% versus 91%) and overall recall is higher in GS: 80% of the references included in the 21 SRs were returned by the original searches in GS versus 68% in PubMed. Only 72% of the included references could be used as they were listed among the first 1,000 hits (the maximum number shown). Practical precision (the number of included references retrieved in the first 1,000, divided by 1,000) was on average 1.9%, which is only slightly lower than in other published SRs. Improving searches with the lowest recall resulted in an increase in recall from 48% to 66% in GS and, in PubMed, from 60% to 85%. Although its coverage and precision are acceptable, GS, because of its incomplete recall, should not be used as a single source in SR searching. A specialized, curated medical database such as PubMed provides experienced searchers with tools and functionality that help improve recall, and numerous options in order to optimize precision. Searches for SRs should be

The comparative recall of Google Scholar versus PubMed in identical searches for biomedical systematic reviews: a review of searches used in systematic reviews

PubMed Central

2013-01-01

Background The usefulness of Google Scholar (GS) as a bibliographic database for biomedical systematic review (SR) searching is a subject of current interest and debate in research circles. Recent research has suggested GS might even be used alone in SR searching. This assertion is challenged here by testing whether GS can locate all studies included in 21 previously published SRs. Second, it examines the recall of GS, taking into account the maximum number of items that can be viewed, and tests whether more complete searches created by an information specialist will improve recall compared to the searches used in the 21 published SRs. Methods The authors identified 21 biomedical SRs that had used GS and PubMed as information sources and reported their use of identical, reproducible search strategies in both databases. These search strategies were rerun in GS and PubMed, and analyzed as to their coverage and recall. Efforts were made to improve searches that underperformed in each database. Results GS’ overall coverage was higher than PubMed (98% versus 91%) and overall recall is higher in GS: 80% of the references included in the 21 SRs were returned by the original searches in GS versus 68% in PubMed. Only 72% of the included references could be used as they were listed among the first 1,000 hits (the maximum number shown). Practical precision (the number of included references retrieved in the first 1,000, divided by 1,000) was on average 1.9%, which is only slightly lower than in other published SRs. Improving searches with the lowest recall resulted in an increase in recall from 48% to 66% in GS and, in PubMed, from 60% to 85%. Conclusions Although its coverage and precision are acceptable, GS, because of its incomplete recall, should not be used as a single source in SR searching. A specialized, curated medical database such as PubMed provides experienced searchers with tools and functionality that help improve recall, and numerous options in order to

An information technology emphasis in biomedical informatics education.

PubMed

Kane, Michael D; Brewer, Jeffrey L

2007-02-01

Unprecedented growth in the interdisciplinary domain of biomedical informatics reflects the recent advancements in genomic sequence availability, high-content biotechnology screening systems, as well as the expectations of computational biology to command a leading role in drug discovery and disease characterization. These forces have moved much of life sciences research almost completely into the computational domain. Importantly, educational training in biomedical informatics has been limited to students enrolled in the life sciences curricula, yet much of the skills needed to succeed in biomedical informatics involve or augment training in information technology curricula. This manuscript describes the methods and rationale for training students enrolled in information technology curricula in the field of biomedical informatics, which augments the existing information technology curriculum and provides training on specific subjects in Biomedical Informatics not emphasized in bioinformatics courses offered in life science programs, and does not require prerequisite courses in the life sciences.

Improving biomedical information retrieval by linear combinations of different query expansion techniques.

PubMed

Abdulla, Ahmed AbdoAziz Ahmed; Lin, Hongfei; Xu, Bo; Banbhrani, Santosh Kumar

2016-07-25

Biomedical literature retrieval is becoming increasingly complex, and there is a fundamental need for advanced information retrieval systems. Information Retrieval (IR) programs scour unstructured materials such as text documents in large reserves of data that are usually stored on computers. IR is related to the representation, storage, and organization of information items, as well as to access. In IR one of the main problems is to determine which documents are relevant and which are not to the user's needs. Under the current regime, users cannot precisely construct queries in an accurate way to retrieve particular pieces of data from large reserves of data. Basic information retrieval systems are producing low-quality search results. In our proposed system for this paper we present a new technique to refine Information Retrieval searches to better represent the user's information need in order to enhance the performance of information retrieval by using different query expansion techniques and apply a linear combinations between them, where the combinations was linearly between two expansion results at one time. Query expansions expand the search query, for example, by finding synonyms and reweighting original terms. They provide significantly more focused, particularized search results than do basic search queries. The retrieval performance is measured by some variants of MAP (Mean Average Precision) and according to our experimental results, the combination of best results of query expansion is enhanced the retrieved documents and outperforms our baseline by 21.06 %, even it outperforms a previous study by 7.12 %. We propose several query expansion techniques and their combinations (linearly) to make user queries more cognizable to search engines and to produce higher-quality search results.

Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature.

PubMed

Müller, H-M; Van Auken, K M; Li, Y; Sternberg, P W

2018-03-09

The biomedical literature continues to grow at a rapid pace, making the challenge of knowledge retrieval and extraction ever greater. Tools that provide a means to search and mine the full text of literature thus represent an important way by which the efficiency of these processes can be improved. We describe the next generation of the Textpresso information retrieval system, Textpresso Central (TPC). TPC builds on the strengths of the original system by expanding the full text corpus to include the PubMed Central Open Access Subset (PMC OA), as well as the WormBase C. elegans bibliography. In addition, TPC allows users to create a customized corpus by uploading and processing documents of their choosing. TPC is UIMA compliant, to facilitate compatibility with external processing modules, and takes advantage of Lucene indexing and search technology for efficient handling of millions of full text documents. Like Textpresso, TPC searches can be performed using keywords and/or categories (semantically related groups of terms), but to provide better context for interpreting and validating queries, search results may now be viewed as highlighted passages in the context of full text. To facilitate biocuration efforts, TPC also allows users to select text spans from the full text and annotate them, create customized curation forms for any data type, and send resulting annotations to external curation databases. As an example of such a curation form, we describe integration of TPC with the Noctua curation tool developed by the Gene Ontology (GO) Consortium. Textpresso Central is an online literature search and curation platform that enables biocurators and biomedical researchers to search and mine the full text of literature by integrating keyword and category searches with viewing search results in the context of the full text. It also allows users to create customized curation interfaces, use those interfaces to make annotations linked to supporting evidence statements

Objective and automated protocols for the evaluation of biomedical search engines using No Title Evaluation protocols.

PubMed

Campagne, Fabien

2008-02-29

The evaluation of information retrieval techniques has traditionally relied on human judges to determine which documents are relevant to a query and which are not. This protocol is used in the Text Retrieval Evaluation Conference (TREC), organized annually for the past 15 years, to support the unbiased evaluation of novel information retrieval approaches. The TREC Genomics Track has recently been introduced to measure the performance of information retrieval for biomedical applications. We describe two protocols for evaluating biomedical information retrieval techniques without human relevance judgments. We call these protocols No Title Evaluation (NT Evaluation). The first protocol measures performance for focused searches, where only one relevant document exists for each query. The second protocol measures performance for queries expected to have potentially many relevant documents per query (high-recall searches). Both protocols take advantage of the clear separation of titles and abstracts found in Medline. We compare the performance obtained with these evaluation protocols to results obtained by reusing the relevance judgments produced in the 2004 and 2005 TREC Genomics Track and observe significant correlations between performance rankings generated by our approach and TREC. Spearman's correlation coefficients in the range of 0.79-0.92 are observed comparing bpref measured with NT Evaluation or with TREC evaluations. For comparison, coefficients in the range 0.86-0.94 can be observed when evaluating the same set of methods with data from two independent TREC Genomics Track evaluations. We discuss the advantages of NT Evaluation over the TRels and the data fusion evaluation protocols introduced recently. Our results suggest that the NT Evaluation protocols described here could be used to optimize some search engine parameters before human evaluation. Further research is needed to determine if NT Evaluation or variants of these protocols can fully substitute

Development of an information retrieval tool for biomedical patents.

PubMed

Alves, Tiago; Rodrigues, Rúben; Costa, Hugo; Rocha, Miguel

2018-06-01

The volume of biomedical literature has been increasing in the last years. Patent documents have also followed this trend, being important sources of biomedical knowledge, technical details and curated data, which are put together along the granting process. The field of Biomedical text mining (BioTM) has been creating solutions for the problems posed by the unstructured nature of natural language, which makes the search of information a challenging task. Several BioTM techniques can be applied to patents. From those, Information Retrieval (IR) includes processes where relevant data are obtained from collections of documents. In this work, the main goal was to build a patent pipeline addressing IR tasks over patent repositories to make these documents amenable to BioTM tasks. The pipeline was developed within @Note2, an open-source computational framework for BioTM, adding a number of modules to the core libraries, including patent metadata and full text retrieval, PDF to text conversion and optical character recognition. Also, user interfaces were developed for the main operations materialized in a new @Note2 plug-in. The integration of these tools in @Note2 opens opportunities to run BioTM tools over patent texts, including tasks from Information Extraction, such as Named Entity Recognition or Relation Extraction. We demonstrated the pipeline's main functions with a case study, using an available benchmark dataset from BioCreative challenges. Also, we show the use of the plug-in with a user query related to the production of vanillin. This work makes available all the relevant content from patents to the scientific community, decreasing drastically the time required for this task, and provides graphical interfaces to ease the use of these tools. Copyright © 2018 Elsevier B.V. All rights reserved.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

PubMed Central

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

Understanding PubMed user search behavior through log analysis.

PubMed

Islamaj Dogan, Rezarta; Murray, G Craig; Névéol, Aurélie; Lu, Zhiyong

2009-01-01

This article reports on a detailed investigation of PubMed users' needs and behavior as a step toward improving biomedical information retrieval. PubMed is providing free service to researchers with access to more than 19 million citations for biomedical articles from MEDLINE and life science journals. It is accessed by millions of users each day. Efficient search tools are crucial for biomedical researchers to keep abreast of the biomedical literature relating to their own research. This study provides insight into PubMed users' needs and their behavior. This investigation was conducted through the analysis of one month of log data, consisting of more than 23 million user sessions and more than 58 million user queries. Multiple aspects of users' interactions with PubMed are characterized in detail with evidence from these logs. Despite having many features in common with general Web searches, biomedical information searches have unique characteristics that are made evident in this study. PubMed users are more persistent in seeking information and they reformulate queries often. The three most frequent types of search are search by author name, search by gene/protein, and search by disease. Use of abbreviation in queries is very frequent. Factors such as result set size influence users' decisions. Analysis of characteristics such as these plays a critical role in identifying users' information needs and their search habits. In turn, such an analysis also provides useful insight for improving biomedical information retrieval.Database URL:http://www.ncbi.nlm.nih.gov/PubMed.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

Modeling and mining term association for improving biomedical information retrieval performance.

PubMed

Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

2012-06-11

The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent

Modeling and mining term association for improving biomedical information retrieval performance

PubMed Central

2012-01-01

Background The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. Results We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. Conclusions First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind

Unsupervised discovery of information structure in biomedical documents.

PubMed

Kiela, Douwe; Guo, Yufan; Stenius, Ulla; Korhonen, Anna

2015-04-01

Information structure (IS) analysis is a text mining technique, which classifies text in biomedical articles into categories that capture different types of information, such as objectives, methods, results and conclusions of research. It is a highly useful technique that can support a range of Biomedical Text Mining tasks and can help readers of biomedical literature find information of interest faster, accelerating the highly time-consuming process of literature review. Several approaches to IS analysis have been presented in the past, with promising results in real-world biomedical tasks. However, all existing approaches, even weakly supervised ones, require several hundreds of hand-annotated training sentences specific to the domain in question. Because biomedicine is subject to considerable domain variation, such annotations are expensive to obtain. This makes the application of IS analysis across biomedical domains difficult. In this article, we investigate an unsupervised approach to IS analysis and evaluate the performance of several unsupervised methods on a large corpus of biomedical abstracts collected from PubMed. Our best unsupervised algorithm (multilevel-weighted graph clustering algorithm) performs very well on the task, obtaining over 0.70 F scores for most IS categories when applied to well-known IS schemes. This level of performance is close to that of lightly supervised IS methods and has proven sufficient to aid a range of practical tasks. Thus, using an unsupervised approach, IS could be applied to support a wide range of tasks across sub-domains of biomedicine. We also demonstrate that unsupervised learning brings novel insights into IS of biomedical literature and discovers information categories that are not present in any of the existing IS schemes. The annotated corpus and software are available at http://www.cl.cam.ac.uk/∼dk427/bio14info.html. © The Author 2014. Published by Oxford University Press. All rights reserved. For

Information Retrieval in Biomedical Research: From Articles to Datasets

ERIC Educational Resources Information Center

Wei, Wei

2017-01-01

Information retrieval techniques have been applied to biomedical research for a variety of purposes, such as textual document retrieval and molecular data retrieval. As biomedical research evolves over time, information retrieval is also constantly facing new challenges, including the growing number of available data, the emerging new data types,…

Cluster-Based Query Expansion Using Language Modeling for Biomedical Literature Retrieval

ERIC Educational Resources Information Center

Xu, Xuheng

2011-01-01

The tremendously huge volume of biomedical literature, scientists' specific information needs, long terms of multiples words, and fundamental problems of synonym and polysemy have been challenging issues facing the biomedical information retrieval community researchers. Search engines have significantly improved the efficiency and effectiveness of…

Preliminary comparison of the Essie and PubMed search engines for answering clinical questions using MD on Tap, a PDA-based program for accessing biomedical literature

PubMed Central

Sutton, Victoria R.; Hauser, Susan E.

2005-01-01

MD on Tap, a PDA application that searches and retrieves biomedical literature, is specifically designed for use by mobile healthcare professionals. With the goal of improving the usability of the application, a preliminary comparison was made of two search engines (PubMed and Essie) to determine which provided most efficient path to the desired clinically-relevant information. PMID:16779415

Preliminary comparison of the Essie and PubMed search engines for answering clinical questions using MD on Tap, a PDA-based program for accessing biomedical literature.

PubMed

Sutton, Victoria R; Hauser, Susan E

2005-01-01

MD on Tap, a PDA application that searches and retrieves biomedical literature, is specifically designed for use by mobile healthcare professionals. With the goal of improving the usability of the application, a preliminary comparison was made of two search engines (PubMed and Essie) to determine which provided most efficient path to the desired clinically-relevant information.

Information needs and information seeking in a biomedical research setting: a study of scientists and science administrators.

PubMed

Grefsheim, Suzanne F; Rankin, Jocelyn A

2007-10-01

An information needs study of clinical specialists and biomedical researchers was conducted at the US National Institutes of Health (NIH) to inform library services and contribute to a broader understanding of information use in academic and research settings. A random stratified sample by job category of 500 NIH scientists was surveyed by telephone by an independent consultant using a standardized information industry instrument, augmented with locally developed questions. Results were analyzed for statistical significance using t- tests and chi square. Findings were compared with published studies and an aggregated dataset of information users in business, government, and health care from Outsell. The study results highlighted similarities and differences with other studies and the industry standard, providing insights into user preferences, including new technologies. NIH scientists overwhelmingly used the NIH Library (424/500), began their searches at the library's Website rather than Google (P = or< 0.001), were likely to seek information themselves (474/500), and valued desktop resources and services. While NIH staff work in a unique setting, they share some information characteristics with other researchers. The findings underscored the need to continue assessing specialized needs and seek innovative solutions. The study led to improvements or expansion of services such as developing a Website search engine, organizing gene sequence data, and assisting with manuscript preparation.

Development and evaluation of a biomedical search engine using a predicate-based vector space model.

PubMed

Kwak, Myungjae; Leroy, Gondy; Martinez, Jesse D; Harwell, Jeffrey

2013-10-01

Although biomedical information available in articles and patents is increasing exponentially, we continue to rely on the same information retrieval methods and use very few keywords to search millions of documents. We are developing a fundamentally different approach for finding much more precise and complete information with a single query using predicates instead of keywords for both query and document representation. Predicates are triples that are more complex datastructures than keywords and contain more structured information. To make optimal use of them, we developed a new predicate-based vector space model and query-document similarity function with adjusted tf-idf and boost function. Using a test bed of 107,367 PubMed abstracts, we evaluated the first essential function: retrieving information. Cancer researchers provided 20 realistic queries, for which the top 15 abstracts were retrieved using a predicate-based (new) and keyword-based (baseline) approach. Each abstract was evaluated, double-blind, by cancer researchers on a 0-5 point scale to calculate precision (0 versus higher) and relevance (0-5 score). Precision was significantly higher (p<.001) for the predicate-based (80%) than for the keyword-based (71%) approach. Relevance was almost doubled with the predicate-based approach-2.1 versus 1.6 without rank order adjustment (p<.001) and 1.34 versus 0.98 with rank order adjustment (p<.001) for predicate--versus keyword-based approach respectively. Predicates can support more precise searching than keywords, laying the foundation for rich and sophisticated information search. Copyright © 2013 Elsevier Inc. All rights reserved.

[Advanced online search techniques and dedicated search engines for physicians].

PubMed

Nahum, Yoav

2008-02-01

In recent years search engines have become an essential tool in the work of physicians. This article will review advanced search techniques from the world of information specialists, as well as some advanced search engine operators that may help physicians improve their online search capabilities, and maximize the yield of their searches. This article also reviews popular dedicated scientific and biomedical literature search engines.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

Biomedical Information Dissemination: Alternative Systems.

ERIC Educational Resources Information Center

Farquhar, J. A.

This memorandum is the result of an investigation into the three existing biomedical information services; MEDLARS (Medical Literature Analysis and Retrieval System), the interlibrary loan (ILL) service, and the network of Poison Control Centers. This research is intended to provide an understanding of the structure, quality, and coverage of these…

Crossing the Chasm: Information Technology to Biomedical Informatics

PubMed Central

Fahy, Brenda G.; Balke, C. William; Umberger, Gloria H.; Talbert, Jeffery; Canales, Denise Niles; Steltenkamp, Carol L.; Conigliaro, Joseph

2011-01-01

Accelerating the translation of new scientific discoveries to improve human health and disease management is the overall goal of a series of initiatives integrated in the National Institutes of Health (NIH) “Roadmap for Medical Research.” The Clinical and Translational Research Award (CTSA) program is, arguably, the most visible component of the NIH Roadmap providing resources to institutions to transform their clinical and translational research enterprises along the goals of the Roadmap. The CTSA program emphasizes biomedical informatics as a critical component for the accomplishment of the NIH’s translational objectives. To be optimally effective, emerging biomedical informatics programs must link with the information technology (IT) platforms of the enterprise clinical operations within academic health centers. This report details one academic health center’s transdisciplinary initiative to create an integrated academic discipline of biomedical informatics through the development of its infrastructure for clinical and translational science infrastructure and response to the CTSA mechanism. This approach required a detailed informatics strategy to accomplish these goals. This transdisciplinary initiative was the impetus for creation of a specialized biomedical informatics core, the Center for Biomedical Informatics (CBI). Development of the CBI codified the need to incorporate medical informatics including quality and safety informatics and enterprise clinical information systems within the CBI. This paper describes the steps taken to develop the biomedical informatics infrastructure, its integration with clinical systems at one academic health center, successes achieved, and barriers encountered during these efforts. PMID:21383632

Crossing the chasm: information technology to biomedical informatics.

PubMed

Fahy, Brenda G; Balke, C William; Umberger, Gloria H; Talbert, Jeffery; Canales, Denise Niles; Steltenkamp, Carol L; Conigliaro, Joseph

2011-06-01

Accelerating the translation of new scientific discoveries to improve human health and disease management is the overall goal of a series of initiatives integrated in the National Institutes of Health (NIH) "Roadmap for Medical Research." The Clinical and Translational Science Award (CTSA) program is, arguably, the most visible component of the NIH Roadmap providing resources to institutions to transform their clinical and translational research enterprises along the goals of the Roadmap. The CTSA program emphasizes biomedical informatics as a critical component for the accomplishment of the NIH's translational objectives. To be optimally effective, emerging biomedical informatics programs must link with the information technology platforms of the enterprise clinical operations within academic health centers.This report details one academic health center's transdisciplinary initiative to create an integrated academic discipline of biomedical informatics through the development of its infrastructure for clinical and translational science infrastructure and response to the CTSA mechanism. This approach required a detailed informatics strategy to accomplish these goals. This transdisciplinary initiative was the impetus for creation of a specialized biomedical informatics core, the Center for Biomedical Informatics (CBI). Development of the CBI codified the need to incorporate medical informatics including quality and safety informatics and enterprise clinical information systems within the CBI. This article describes the steps taken to develop the biomedical informatics infrastructure, its integration with clinical systems at one academic health center, successes achieved, and barriers encountered during these efforts.

Task-Based Information Searching.

ERIC Educational Resources Information Center

Vakkari, Pertti

2003-01-01

Reviews studies on the relationship between task performance and information searching by end-users, focusing on information searching in electronic environments and information retrieval systems. Topics include task analysis; task characteristics; search goals; modeling information searching; modeling search goals; information seeking behavior;…

A Part-Of-Speech term weighting scheme for biomedical information retrieval.

PubMed

Wang, Yanshan; Wu, Stephen; Li, Dingcheng; Mehrabi, Saeed; Liu, Hongfang

2016-10-01

In the era of digitalization, information retrieval (IR), which retrieves and ranks documents from large collections according to users' search queries, has been popularly applied in the biomedical domain. Building patient cohorts using electronic health records (EHRs) and searching literature for topics of interest are some IR use cases. Meanwhile, natural language processing (NLP), such as tokenization or Part-Of-Speech (POS) tagging, has been developed for processing clinical documents or biomedical literature. We hypothesize that NLP can be incorporated into IR to strengthen the conventional IR models. In this study, we propose two NLP-empowered IR models, POS-BoW and POS-MRF, which incorporate automatic POS-based term weighting schemes into bag-of-word (BoW) and Markov Random Field (MRF) IR models, respectively. In the proposed models, the POS-based term weights are iteratively calculated by utilizing a cyclic coordinate method where golden section line search algorithm is applied along each coordinate to optimize the objective function defined by mean average precision (MAP). In the empirical experiments, we used the data sets from the Medical Records track in Text REtrieval Conference (TREC) 2011 and 2012 and the Genomics track in TREC 2004. The evaluation on TREC 2011 and 2012 Medical Records tracks shows that, for the POS-BoW models, the mean improvement rates for IR evaluation metrics, MAP, bpref, and P@10, are 10.88%, 4.54%, and 3.82%, compared to the BoW models; and for the POS-MRF models, these rates are 13.59%, 8.20%, and 8.78%, compared to the MRF models. Additionally, we experimentally verify that the proposed weighting approach is superior to the simple heuristic and frequency based weighting approaches, and validate our POS category selection. Using the optimal weights calculated in this experiment, we tested the proposed models on the TREC 2004 Genomics track and obtained average of 8.63% and 10.04% improvement rates for POS-BoW and POS

Semantic similarity measure in biomedical domain leverage web search engine.

PubMed

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

A concept-based interactive biomedical image retrieval approach using visualness and spatial information

NASA Astrophysics Data System (ADS)

Rahman, Md M.; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

This paper presents a novel approach to biomedical image retrieval by mapping image regions to local concepts and represent images in a weighted entropy-based concept feature space. The term concept refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist user in interactively select a Region-Of-Interest (ROI) and search for similar image ROIs. Further, a spatial verification step is used as a post-processing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval, is validated through experiments on a data set of 450 lung CT images extracted from journal articles from four different collections.

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development.

PubMed

McEntire, Robin; Szalkowski, Debbie; Butler, James; Kuo, Michelle S; Chang, Meiping; Chang, Man; Freeman, Darren; McQuay, Sarah; Patel, Jagruti; McGlashen, Michael; Cornell, Wendy D; Xu, Jinghai James

2016-05-01

External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources. Copyright © 2016. Published by Elsevier Ltd.

Electronic Biomedical Literature Search for Budding Researcher

PubMed Central

Thakre, Subhash B.; Thakre S, Sushama S.; Thakre, Amol D.

2013-01-01

Search for specific and well defined literature related to subject of interest is the foremost step in research. When we are familiar with topic or subject then we can frame appropriate research question. Appropriate research question is the basis for study objectives and hypothesis. The Internet provides a quick access to an overabundance of the medical literature, in the form of primary, secondary and tertiary literature. It is accessible through journals, databases, dictionaries, textbooks, indexes, and e-journals, thereby allowing access to more varied, individualised, and systematic educational opportunities. Web search engine is a tool designed to search for information on the World Wide Web, which may be in the form of web pages, images, information, and other types of files. Search engines for internet-based search of medical literature include Google, Google scholar, Scirus, Yahoo search engine, etc., and databases include MEDLINE, PubMed, MEDLARS, etc. Several web-libraries (National library Medicine, Cochrane, Web of Science, Medical matrix, Emory libraries) have been developed as meta-sites, providing useful links to health resources globally. A researcher must keep in mind the strengths and limitations of a particular search engine/database while searching for a particular type of data. Knowledge about types of literature, levels of evidence, and detail about features of search engine as available, user interface, ease of access, reputable content, and period of time covered allow their optimal use and maximal utility in the field of medicine. Literature search is a dynamic and interactive process; there is no one way to conduct a search and there are many variables involved. It is suggested that a systematic search of literature that uses available electronic resource effectively, is more likely to produce quality research. PMID:24179937

Electronic biomedical literature search for budding researcher.

PubMed

Thakre, Subhash B; Thakre S, Sushama S; Thakre, Amol D

2013-09-01

Search for specific and well defined literature related to subject of interest is the foremost step in research. When we are familiar with topic or subject then we can frame appropriate research question. Appropriate research question is the basis for study objectives and hypothesis. The Internet provides a quick access to an overabundance of the medical literature, in the form of primary, secondary and tertiary literature. It is accessible through journals, databases, dictionaries, textbooks, indexes, and e-journals, thereby allowing access to more varied, individualised, and systematic educational opportunities. Web search engine is a tool designed to search for information on the World Wide Web, which may be in the form of web pages, images, information, and other types of files. Search engines for internet-based search of medical literature include Google, Google scholar, Scirus, Yahoo search engine, etc., and databases include MEDLINE, PubMed, MEDLARS, etc. Several web-libraries (National library Medicine, Cochrane, Web of Science, Medical matrix, Emory libraries) have been developed as meta-sites, providing useful links to health resources globally. A researcher must keep in mind the strengths and limitations of a particular search engine/database while searching for a particular type of data. Knowledge about types of literature, levels of evidence, and detail about features of search engine as available, user interface, ease of access, reputable content, and period of time covered allow their optimal use and maximal utility in the field of medicine. Literature search is a dynamic and interactive process; there is no one way to conduct a search and there are many variables involved. It is suggested that a systematic search of literature that uses available electronic resource effectively, is more likely to produce quality research.

Utilization of ontology look-up services in information retrieval for biomedical literature.

PubMed

Vishnyakova, Dina; Pasche, Emilie; Lovis, Christian; Ruch, Patrick

2013-01-01

With the vast amount of biomedical data we face the necessity to improve information retrieval processes in biomedical domain. The use of biomedical ontologies facilitated the combination of various data sources (e.g. scientific literature, clinical data repository) by increasing the quality of information retrieval and reducing the maintenance efforts. In this context, we developed Ontology Look-up services (OLS), based on NEWT and MeSH vocabularies. Our services were involved in some information retrieval tasks such as gene/disease normalization. The implementation of OLS services significantly accelerated the extraction of particular biomedical facts by structuring and enriching the data context. The results of precision in normalization tasks were boosted on about 20%.

User needs analysis and usability assessment of DataMed - a biomedical data discovery index.

PubMed

Dixit, Ram; Rogith, Deevakar; Narayana, Vidya; Salimi, Mandana; Gururaj, Anupama; Ohno-Machado, Lucila; Xu, Hua; Johnson, Todd R

2017-11-30

To present user needs and usability evaluations of DataMed, a Data Discovery Index (DDI) that allows searching for biomedical data from multiple sources. We conducted 2 phases of user studies. Phase 1 was a user needs analysis conducted before the development of DataMed, consisting of interviews with researchers. Phase 2 involved iterative usability evaluations of DataMed prototypes. We analyzed data qualitatively to document researchers' information and user interface needs. Biomedical researchers' information needs in data discovery are complex, multidimensional, and shaped by their context, domain knowledge, and technical experience. User needs analyses validate the need for a DDI, while usability evaluations of DataMed show that even though aggregating metadata into a common search engine and applying traditional information retrieval tools are promising first steps, there remain challenges for DataMed due to incomplete metadata and the complexity of data discovery. Biomedical data poses distinct problems for search when compared to websites or publications. Making data available is not enough to facilitate biomedical data discovery: new retrieval techniques and user interfaces are necessary for dataset exploration. Consistent, complete, and high-quality metadata are vital to enable this process. While available data and researchers' information needs are complex and heterogeneous, a successful DDI must meet those needs and fit into the processes of biomedical researchers. Research directions include formalizing researchers' information needs, standardizing overviews of data to facilitate relevance judgments, implementing user interfaces for concept-based searching, and developing evaluation methods for open-ended discovery systems such as DDIs. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Introducing meta-services for biomedical information extraction

PubMed Central

Leitner, Florian; Krallinger, Martin; Rodriguez-Penagos, Carlos; Hakenberg, Jörg; Plake, Conrad; Kuo, Cheng-Ju; Hsu, Chun-Nan; Tsai, Richard Tzong-Han; Hung, Hsi-Chuan; Lau, William W; Johnson, Calvin A; Sætre, Rune; Yoshida, Kazuhiro; Chen, Yan Hua; Kim, Sun; Shin, Soo-Yong; Zhang, Byoung-Tak; Baumgartner, William A; Hunter, Lawrence; Haddow, Barry; Matthews, Michael; Wang, Xinglong; Ruch, Patrick; Ehrler, Frédéric; Özgür, Arzucan; Erkan, Güneş; Radev, Dragomir R; Krauthammer, Michael; Luong, ThaiBinh; Hoffmann, Robert; Sander, Chris; Valencia, Alfonso

2008-01-01

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations. PMID:18834497

Should we search Chinese biomedical databases when performing systematic reviews?

PubMed

Cohen, Jérémie F; Korevaar, Daniël A; Wang, Junfeng; Spijker, René; Bossuyt, Patrick M

2015-03-06

Chinese biomedical databases contain a large number of publications available to systematic reviewers, but it is unclear whether they are used for synthesizing the available evidence. We report a case of two systematic reviews on the accuracy of anti-cyclic citrullinated peptide for diagnosing rheumatoid arthritis. In one of these, the authors did not search Chinese databases; in the other, they did. We additionally assessed the extent to which Cochrane reviewers have searched Chinese databases in a systematic overview of the Cochrane Library (inception to 2014). The two diagnostic reviews included a total of 269 unique studies, but only 4 studies were included in both reviews. The first review included five studies published in the Chinese language (out of 151) while the second included 114 (out of 118). The summary accuracy estimates from the two reviews were comparable. Only 243 of the published 8,680 Cochrane reviews (less than 3%) searched one or more of the five major Chinese databases. These Chinese databases index about 2,500 journals, of which less than 6% are also indexed in MEDLINE. All 243 Cochrane reviews evaluated an intervention, 179 (74%) had at least one author with a Chinese affiliation; 118 (49%) addressed a topic in complementary or alternative medicine. Although searching Chinese databases may lead to the identification of a large amount of additional clinical evidence, Cochrane reviewers have rarely included them in their search strategy. We encourage future initiatives to evaluate more systematically the relevance of searching Chinese databases, as well as collaborative efforts to allow better incorporation of Chinese resources in systematic reviews.

Improving average ranking precision in user searches for biomedical research datasets

PubMed Central

Gobeill, Julien; Gaudinat, Arnaud; Vachon, Thérèse; Ruch, Patrick

2017-01-01

Abstract Availability of research datasets is keystone for health and life science study reproducibility and scientific progress. Due to the heterogeneity and complexity of these data, a main challenge to be overcome by research data management systems is to provide users with the best answers for their search queries. In the context of the 2016 bioCADDIE Dataset Retrieval Challenge, we investigate a novel ranking pipeline to improve the search of datasets used in biomedical experiments. Our system comprises a query expansion model based on word embeddings, a similarity measure algorithm that takes into consideration the relevance of the query terms, and a dataset categorization method that boosts the rank of datasets matching query constraints. The system was evaluated using a corpus with 800k datasets and 21 annotated user queries, and provided competitive results when compared to the other challenge participants. In the official run, it achieved the highest infAP, being +22.3% higher than the median infAP of the participant’s best submissions. Overall, it is ranked at top 2 if an aggregated metric using the best official measures per participant is considered. The query expansion method showed positive impact on the system’s performance increasing our baseline up to +5.0% and +3.4% for the infAP and infNDCG metrics, respectively. The similarity measure algorithm showed robust performance in different training conditions, with small performance variations compared to the Divergence from Randomness framework. Finally, the result categorization did not have significant impact on the system’s performance. We believe that our solution could be used to enhance biomedical dataset management systems. The use of data driven expansion methods, such as those based on word embeddings, could be an alternative to the complexity of biomedical terminologies. Nevertheless, due to the limited size of the assessment set, further experiments need to be performed to draw

A passage retrieval method based on probabilistic information retrieval model and UMLS concepts in biomedical question answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-04-01

Passage retrieval, the identification of top-ranked passages that may contain the answer for a given biomedical question, is a crucial component for any biomedical question answering (QA) system. Passage retrieval in open-domain QA is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in biomedical QA. In this paper, we present a new biomedical passage retrieval method based on Stanford CoreNLP sentence/passage length, probabilistic information retrieval (IR) model and UMLS concepts. In the proposed method, we first use our document retrieval system based on PubMed search engine and UMLS similarity to retrieve relevant documents to a given biomedical question. We then take the abstracts from the retrieved documents and use Stanford CoreNLP for sentence splitter to make a set of sentences, i.e., candidate passages. Using stemmed words and UMLS concepts as features for the BM25 model, we finally compute the similarity scores between the biomedical question and each of the candidate passages and keep the N top-ranked ones. Experimental evaluations performed on large standard datasets, provided by the BioASQ challenge, show that the proposed method achieves good performances compared with the current state-of-the-art methods. The proposed method significantly outperforms the current state-of-the-art methods by an average of 6.84% in terms of mean average precision (MAP). We have proposed an efficient passage retrieval method which can be used to retrieve relevant passages in biomedical QA systems with high mean average precision. Copyright © 2017 Elsevier Inc. All rights reserved.

Extracting semantically enriched events from biomedical literature

PubMed Central

2012-01-01

Background Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Results Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP’09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP’09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. Conclusions We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information

Extracting semantically enriched events from biomedical literature.

PubMed

Miwa, Makoto; Thompson, Paul; McNaught, John; Kell, Douglas B; Ananiadou, Sophia

2012-05-23

Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP'09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP'09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information can be used to refine search systems

PASSIM--an open source software system for managing information in biomedical studies.

PubMed

Viksna, Juris; Celms, Edgars; Opmanis, Martins; Podnieks, Karlis; Rucevskis, Peteris; Zarins, Andris; Barrett, Amy; Neogi, Sudeshna Guha; Krestyaninova, Maria; McCarthy, Mark I; Brazma, Alvis; Sarkans, Ugis

2007-02-09

One of the crucial aspects of day-to-day laboratory information management is collection, storage and retrieval of information about research subjects and biomedical samples. An efficient link between sample data and experiment results is absolutely imperative for a successful outcome of a biomedical study. Currently available software solutions are largely limited to large-scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but often implies sufficient investment of time, effort and funds, which are not always available. There is a clear need for lightweight open source systems for patient and sample information management. We present a web-based tool for submission, management and retrieval of sample and research subject data. The system secures confidentiality by separating anonymized sample information from individuals' records. It is simple and generic, and can be customised for various biomedical studies. Information can be both entered and accessed using the same web interface. User groups and their privileges can be defined. The system is open-source and is supplied with an on-line tutorial and necessary documentation. It has proven to be successful in a large international collaborative project. The presented system closes the gap between the need and the availability of lightweight software solutions for managing information in biomedical studies involving human research subjects.

Tackling the challenges of matching biomedical ontologies.

PubMed

Faria, Daniel; Pesquita, Catia; Mott, Isabela; Martins, Catarina; Couto, Francisco M; Cruz, Isabel F

2018-01-15

Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development of matching systems able to tackle these challenges, and benchmarked their general performance. In this study, we dissect the strategies employed by matching systems to tackle the challenges of matching biomedical ontologies and gauge the impact of the challenges themselves on matching performance, using the AgreementMakerLight (AML) system as the platform for this study. We demonstrate that the linear complexity of the hash-based searching strategy implemented by most state-of-the-art ontology matching systems is essential for matching large biomedical ontologies efficiently. We show that accounting for all lexical annotations (e.g., labels and synonyms) in biomedical ontologies leads to a substantial improvement in F-measure over using only the primary name, and that accounting for the reliability of different types of annotations generally also leads to a marked improvement. Finally, we show that cross-references are a reliable source of information and that, when using biomedical ontologies as background knowledge, it is generally more reliable to use them as mediators than to perform lexical expansion. We anticipate that translating traditional matching algorithms to the hash-based searching paradigm will be a critical direction for the future development of the field. Improving the evaluation carried out in the biomedical tracks of the OAEI will also be important, as without proper reference alignments there is only so much that can be ascertained about matching systems or strategies. Nevertheless, it is clear that, to tackle the various challenges posed by biomedical ontologies, ontology matching systems must be able to efficiently combine multiple strategies into a mature matching

Biomedical Computing Technology Information Center: introduction and report of early progress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maskewitz, B.F.; Henne, R.L.; McClain, W.J.

1976-01-01

In July 1975, the Biomedical Computing Technology Information Center (BCTIC) was established by the Division of Biomedical and Environmental Research of the U. S. Energy Research and Development Administration (ERDA) at the Oak Ridge National Laboratory. BCTIC collects, organizes, evaluates, and disseminates information on computing technology pertinent to biomedicine, providing needed routes of communication between installations and serving as a clearinghouse for the exchange of biomedical computing software, data, and interface designs. This paper presents BCTIC's functions and early progress to the MUMPS Users' Group in order to stimulate further discussion and cooperation between the two organizations. (BCTIC services aremore » available to its sponsors and their contractors and to any individual/group willing to participate in mutual exchange.) 1 figure.« less

A method for exploring implicit concept relatedness in biomedical knowledge network.

PubMed

Bai, Tian; Gong, Leiguang; Wang, Ye; Wang, Yan; Kulikowski, Casimir A; Huang, Lan

2016-07-19

Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community. In this study, a hybrid biomedical knowledge network is constructed by linking concepts across multiple biomedical ontologies as well as non-structural biomedical knowledge sources. To discover implicit relatedness between concepts in ontologies for which potentially valuable relationships (implicit knowledge) may exist, we developed a Multi-Ontology Relatedness Model (MORM) within the knowledge network, for which a relatedness network (RN) is defined and computed across multiple ontologies using a formal inference mechanism of set-theoretic operations. Semantic constraints are designed and implemented to prune the search space of the relatedness network. Experiments to test examples of several biomedical applications have been carried out, and the evaluation of the results showed an encouraging potential of the proposed approach to biomedical knowledge discovery.

[Ethics of biomedical research: questions about patient information].

PubMed

Moutel, Grégoire

2013-02-01

All recommendations and laws concerning biomedical research, including the most recent in France in 2012, emphasize the quality of patient information to justify its participation. To optimize practices, it is important to take into account the central issues: what limits of information? What role for the relatives and family in the decision in case of disability or vulnerability of a patient? What need for specific information for long protocol and follow-up cohort? What information about research results? © 2013 médecine/sciences – Inserm / SRMS.

DataMed - an open source discovery index for finding biomedical datasets.

PubMed

Chen, Xiaoling; Gururaj, Anupama E; Ozyurt, Burak; Liu, Ruiling; Soysal, Ergin; Cohen, Trevor; Tiryaki, Firat; Li, Yueling; Zong, Nansu; Jiang, Min; Rogith, Deevakar; Salimi, Mandana; Kim, Hyeon-Eui; Rocca-Serra, Philippe; Gonzalez-Beltran, Alejandra; Farcas, Claudiu; Johnson, Todd; Margolis, Ron; Alter, George; Sansone, Susanna-Assunta; Fore, Ian M; Ohno-Machado, Lucila; Grethe, Jeffrey S; Xu, Hua

2018-01-13

Finding relevant datasets is important for promoting data reuse in the biomedical domain, but it is challenging given the volume and complexity of biomedical data. Here we describe the development of an open source biomedical data discovery system called DataMed, with the goal of promoting the building of additional data indexes in the biomedical domain. DataMed, which can efficiently index and search diverse types of biomedical datasets across repositories, is developed through the National Institutes of Health-funded biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) consortium. It consists of 2 main components: (1) a data ingestion pipeline that collects and transforms original metadata information to a unified metadata model, called DatA Tag Suite (DATS), and (2) a search engine that finds relevant datasets based on user-entered queries. In addition to describing its architecture and techniques, we evaluated individual components within DataMed, including the accuracy of the ingestion pipeline, the prevalence of the DATS model across repositories, and the overall performance of the dataset retrieval engine. Our manual review shows that the ingestion pipeline could achieve an accuracy of 90% and core elements of DATS had varied frequency across repositories. On a manually curated benchmark dataset, the DataMed search engine achieved an inferred average precision of 0.2033 and a precision at 10 (P@10, the number of relevant results in the top 10 search results) of 0.6022, by implementing advanced natural language processing and terminology services. Currently, we have made the DataMed system publically available as an open source package for the biomedical community. © The Author 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

PubMed

Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

2015-10-01

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

PubMed Central

Rahman, Md. Mahmudur; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-01-01

Abstract. This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature. PMID:26730398

Pharmacovigilance and Biomedical Informatics: A Model for Future Development.

PubMed

Beninger, Paul; Ibara, Michael A

2016-12-01

The discipline of pharmacovigilance is rooted in the aftermath of the thalidomide tragedy of 1961. It has evolved as a result of collaborative efforts by many individuals and organizations, including physicians, patients, Health Authorities, universities, industry, the World Health Organization, the Council for International Organizations of Medical Sciences, and the International Conference on Harmonisation. Biomedical informatics is rooted in technologically based methodologies and has evolved at the speed of computer technology. The purpose of this review is to bring a novel lens to pharmacovigilance, looking at the evolution and development of the field of pharmacovigilance from the perspective of biomedical informatics, with the explicit goal of providing a foundation for discussion of the future direction of pharmacovigilance as a discipline. For this review, we searched [publication trend for the log 10 value of the numbers of publications identified in PubMed] using the key words [informatics (INF), pharmacovigilance (PV), phar-macovigilance þ informatics (PV þ INF)], for [study types] articles published between [1994-2015]. We manually searched the reference lists of identified articles for additional information. Biomedical informatics has made significant contributions to the infrastructural development of pharmacovigilance. However, there has not otherwise been a systematic assessment of the role of biomedical informatics in enhancing the field of pharmacovigilance, and there has been little cross-discipline scholarship. Rapidly developing innovations in biomedical informatics pose a challenge to pharmacovigilance in finding ways to include new sources of safety information, including social media, massively linked databases, and mobile and wearable wellness applications and sensors. With biomedical informatics as a lens, it is evident that certain aspects of pharmacovigilance are evolving more slowly. However, the high levels of mutual interest in

G-Bean: an ontology-graph based web tool for biomedical literature retrieval.

PubMed

Wang, James Z; Zhang, Yuanyuan; Dong, Liang; Li, Lin; Srimani, Pradip K; Yu, Philip S

2014-01-01

Currently, most people use NCBI's PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently. G-Bean addresses PubMed's limitations with three innovations: (1) Parallel document index creation: a multithreaded index creation strategy is employed to generate the document index for G-Bean in parallel; (2) Ontology-graph based query expansion: an ontology graph is constructed by merging four major UMLS (Version 2013AA) vocabularies, MeSH, SNOMEDCT, CSP and AOD, to cover all concepts in National Library of Medicine (NLM) database; a Personalized PageRank algorithm is used to compute concept relevance in this ontology graph and the Term Frequency - Inverse Document Frequency (TF-IDF) weighting scheme is used to re-rank the concepts. The top 500 ranked concepts are selected for expanding the initial query to retrieve more accurate and relevant information; (3) Retrieval and re-ranking of documents based on user's search intention: after the user selects any article from the existing search results, G-Bean analyzes user's selections to determine his/her true search intention and then uses more relevant and more specific terms to retrieve additional related articles. The new articles are presented to the user in the order of their relevance to the already selected articles. Performance evaluation with 106 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to form the appropriate Boolean

Data management integration for biomedical core facilities

NASA Astrophysics Data System (ADS)

Zhang, Guo-Qiang; Szymanski, Jacek; Wilson, David

2007-03-01

We present the design, development, and pilot-deployment experiences of MIMI, a web-based, Multi-modality Multi-Resource Information Integration environment for biomedical core facilities. This is an easily customizable, web-based software tool that integrates scientific and administrative support for a biomedical core facility involving a common set of entities: researchers; projects; equipments and devices; support staff; services; samples and materials; experimental workflow; large and complex data. With this software, one can: register users; manage projects; schedule resources; bill services; perform site-wide search; archive, back-up, and share data. With its customizable, expandable, and scalable characteristics, MIMI not only provides a cost-effective solution to the overarching data management problem of biomedical core facilities unavailable in the market place, but also lays a foundation for data federation to facilitate and support discovery-driven research.

Finding and accessing diagrams in biomedical publications.

PubMed

Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

2012-01-01

Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts.

Institute for Scientific Information-indexed biomedical journals of Saudi Arabia

PubMed Central

Rohra, Dileep K.; Rohra, Vikram K.; Cahusac, Peter

2016-01-01

Objectives: To compare the journal impact factor (JIF) and Eigenfactor score (ES) of Institute for Scientific Information (ISI)-indexed biomedical journals published from the Kingdom of Saudi Arabia (KSA) over the last 8 years. Methods: This is a retrospective study, conducted at Alfaisal University, Riyadh, KSA from January to March 2016. The Journal Citation Reports of ISI Web of Knowledge were accessed, and 6 Saudi biomedical journals were included for analysis. Results: All Saudi journals have improved their IF compared with their baseline. However, the performance of the Journal of Pharmaceutical Sciences and Neurosciences has been exceptionally good. The biggest improvement in percent growth in JIF was seen in the Saudi Pharmaceutical Journal (approximately 887%) followed by Neurosciences (approximately 462%). Interestingly, the ES of all biomedical journals, except Saudi Journal of Gastroenterology and Saudi Medical Journal, increased over the years. The greatest growth in ES (more than 5 fold) was noted for Neurosciences and Saudi Pharmaceutical Journal. Conclusion: This study shows that the overall quality of all Saudi biomedical journals has improved in the last 8 years. PMID:27761565

Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System

PubMed Central

Myneni, Sahiti; Patel, Vimla L.

2010-01-01

Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers’ time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment. PMID:20543892

Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System.

PubMed

Myneni, Sahiti; Patel, Vimla L

2010-06-01

Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers' time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation

PubMed Central

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as ‘CHEMICAL-1 compared to CHEMICAL-2.’ With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical–disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked

The cost of quality: Implementing generalization and suppression for anonymizing biomedical data with minimal information loss.

PubMed

Kohlmayer, Florian; Prasser, Fabian; Kuhn, Klaus A

2015-12-01

With the ARX data anonymization tool structured biomedical data can be de-identified using syntactic privacy models, such as k-anonymity. Data is transformed with two methods: (a) generalization of attribute values, followed by (b) suppression of data records. The former method results in data that is well suited for analyses by epidemiologists, while the latter method significantly reduces loss of information. Our tool uses an optimal anonymization algorithm that maximizes output utility according to a given measure. To achieve scalability, existing optimal anonymization algorithms exclude parts of the search space by predicting the outcome of data transformations regarding privacy and utility without explicitly applying them to the input dataset. These optimizations cannot be used if data is transformed with generalization and suppression. As optimal data utility and scalability are important for anonymizing biomedical data, we had to develop a novel method. In this article, we first confirm experimentally that combining generalization with suppression significantly increases data utility. Next, we proof that, within this coding model, the outcome of data transformations regarding privacy and utility cannot be predicted. As a consequence, existing algorithms fail to deliver optimal data utility. We confirm this finding experimentally. The limitation of previous work can be overcome at the cost of increased computational complexity. However, scalability is important for anonymizing data with user feedback. Consequently, we identify properties of datasets that may be predicted in our context and propose a novel and efficient algorithm. Finally, we evaluate our solution with multiple datasets and privacy models. This work presents the first thorough investigation of which properties of datasets can be predicted when data is anonymized with generalization and suppression. Our novel approach adopts existing optimization strategies to our context and combines different

Multitasking Information Seeking and Searching Processes.

ERIC Educational Resources Information Center

Spink, Amanda; Ozmutlu, H. Cenk; Ozmutlu, Seda

2002-01-01

Presents findings from four studies of the prevalence of multitasking information seeking and searching by Web (via the Excite search engine), information retrieval system (mediated online database searching), and academic library users. Highlights include human information coordinating behavior (HICB); and implications for models of information…

Key Relation Extraction from Biomedical Publications.

PubMed

Huang, Lan; Wang, Ye; Gong, Leiguang; Kulikowski, Casimir; Bai, Tian

2017-01-01

Within the large body of biomedical knowledge, recent findings and discoveries are most often presented as research articles. Their number has been increasing sharply since the turn of the century, presenting ever-growing challenges for search and discovery of knowledge and information related to specific topics of interest, even with the help of advanced online search tools. This is especially true when the goal of a search is to find or discover key relations between important concepts or topic words. We have developed an innovative method for extracting key relations between concepts from abstracts of articles. The method focuses on relations between keywords or topic words in the articles. Early experiments with the method on PubMed publications have shown promising results in searching and discovering keywords and their relationships that are strongly related to the main topic of an article.

ReVeaLD: a user-driven domain-specific interactive search platform for biomedical research.

PubMed

Kamdar, Maulik R; Zeginis, Dimitris; Hasnain, Ali; Decker, Stefan; Deus, Helena F

2014-02-01

Bioinformatics research relies heavily on the ability to discover and correlate data from various sources. The specialization of life sciences over the past decade, coupled with an increasing number of biomedical datasets available through standardized interfaces, has created opportunities towards new methods in biomedical discovery. Despite the popularity of semantic web technologies in tackling the integrative bioinformatics challenge, there are many obstacles towards its usage by non-technical research audiences. In particular, the ability to fully exploit integrated information needs using improved interactive methods intuitive to the biomedical experts. In this report we present ReVeaLD (a Real-time Visual Explorer and Aggregator of Linked Data), a user-centered visual analytics platform devised to increase intuitive interaction with data from distributed sources. ReVeaLD facilitates query formulation using a domain-specific language (DSL) identified by biomedical experts and mapped to a self-updated catalogue of elements from external sources. ReVeaLD was implemented in a cancer research setting; queries included retrieving data from in silico experiments, protein modeling and gene expression. ReVeaLD was developed using Scalable Vector Graphics and JavaScript and a demo with explanatory video is available at http://www.srvgal78.deri.ie:8080/explorer. A set of user-defined graphic rules controls the display of information through media-rich user interfaces. Evaluation of ReVeaLD was carried out as a game: biomedical researchers were asked to assemble a set of 5 challenge questions and time and interactions with the platform were recorded. Preliminary results indicate that complex queries could be formulated under less than two minutes by unskilled researchers. The results also indicate that supporting the identification of the elements of a DSL significantly increased intuitiveness of the platform and usability of semantic web technologies by domain users

Finding and Accessing Diagrams in Biomedical Publications

PubMed Central

Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

2012-01-01

Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts. PMID:23304318

G-Bean: an ontology-graph based web tool for biomedical literature retrieval

PubMed Central

2014-01-01

Background Currently, most people use NCBI's PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently. Methods G-Bean addresses PubMed's limitations with three innovations: (1) Parallel document index creation: a multithreaded index creation strategy is employed to generate the document index for G-Bean in parallel; (2) Ontology-graph based query expansion: an ontology graph is constructed by merging four major UMLS (Version 2013AA) vocabularies, MeSH, SNOMEDCT, CSP and AOD, to cover all concepts in National Library of Medicine (NLM) database; a Personalized PageRank algorithm is used to compute concept relevance in this ontology graph and the Term Frequency - Inverse Document Frequency (TF-IDF) weighting scheme is used to re-rank the concepts. The top 500 ranked concepts are selected for expanding the initial query to retrieve more accurate and relevant information; (3) Retrieval and re-ranking of documents based on user's search intention: after the user selects any article from the existing search results, G-Bean analyzes user's selections to determine his/her true search intention and then uses more relevant and more specific terms to retrieve additional related articles. The new articles are presented to the user in the order of their relevance to the already selected articles. Results Performance evaluation with 106 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to

SATORI: a system for ontology-guided visual exploration of biomedical data repositories.

PubMed

Lekschas, Fritz; Gehlenborg, Nils

2018-04-01

The ever-increasing number of biomedical datasets provides tremendous opportunities for re-use but current data repositories provide limited means of exploration apart from text-based search. Ontological metadata annotations provide context by semantically relating datasets. Visualizing this rich network of relationships can improve the explorability of large data repositories and help researchers find datasets of interest. We developed SATORI-an integrative search and visual exploration interface for the exploration of biomedical data repositories. The design is informed by a requirements analysis through a series of semi-structured interviews. We evaluated the implementation of SATORI in a field study on a real-world data collection. SATORI enables researchers to seamlessly search, browse and semantically query data repositories via two visualizations that are highly interconnected with a powerful search interface. SATORI is an open-source web application, which is freely available at http://satori.refinery-platform.org and integrated into the Refinery Platform. nils@hms.harvard.edu. Supplementary data are available at Bioinformatics online.

Expert Search Strategies: The Information Retrieval Practices of Healthcare Information Professionals

PubMed Central

2017-01-01

Background Healthcare information professionals play a key role in closing the knowledge gap between medical research and clinical practice. Their work involves meticulous searching of literature databases using complex search strategies that can consist of hundreds of keywords, operators, and ontology terms. This process is prone to error and can lead to inefficiency and bias if performed incorrectly. Objective The aim of this study was to investigate the search behavior of healthcare information professionals, uncovering their needs, goals, and requirements for information retrieval systems. Methods A survey was distributed to healthcare information professionals via professional association email discussion lists. It investigated the search tasks they undertake, their techniques for search strategy formulation, their approaches to evaluating search results, and their preferred functionality for searching library-style databases. The popular literature search system PubMed was then evaluated to determine the extent to which their needs were met. Results The 107 respondents indicated that their information retrieval process relied on the use of complex, repeatable, and transparent search strategies. On average it took 60 minutes to formulate a search strategy, with a search task taking 4 hours and consisting of 15 strategy lines. Respondents reviewed a median of 175 results per search task, far more than they would ideally like (100). The most desired features of a search system were merging search queries and combining search results. Conclusions Healthcare information professionals routinely address some of the most challenging information retrieval problems of any profession. However, their needs are not fully supported by current literature search systems and there is demand for improved functionality, in particular regarding the development and management of search strategies. PMID:28970190

Olelo: a web application for intuitive exploration of biomedical literature

PubMed Central

Niedermeier, Julian; Jankrift, Marcel; Tietböhl, Sören; Stachewicz, Toni; Folkerts, Hendrik; Uflacker, Matthias; Neves, Mariana

2017-01-01

Abstract Researchers usually query the large biomedical literature in PubMed via keywords, logical operators and filters, none of which is very intuitive. Question answering systems are an alternative to keyword searches. They allow questions in natural language as input and results reflect the given type of question, such as short answers and summaries. Few of those systems are available online but they experience drawbacks in terms of long response times and they support a limited amount of question and result types. Additionally, user interfaces are usually restricted to only displaying the retrieved information. For our Olelo web application, we combined biomedical literature and terminologies in a fast in-memory database to enable real-time responses to researchers’ queries. Further, we extended the built-in natural language processing features of the database with question answering and summarization procedures. Combined with a new explorative approach of document filtering and a clean user interface, Olelo enables a fast and intelligent search through the ever-growing biomedical literature. Olelo is available at http://www.hpi.de/plattner/olelo. PMID:28472397

Strategies for Disseminating Information on Biomedical Research on Autism to Hispanic Parents

PubMed Central

Lajonchere, Clara M.; Wheeler, Barbara Y.; Valente, Thomas W.; Kreutzer, Cary; Munson, Aron; Narayanan, Shrikanth; Kazemzadeh, Abe; Cruz, Roxana; Martinez, Irene; Schrager, Sheree M.; Schweitzer, Lisa; Chklovski, Tara; Hwang, Darryl

2015-01-01

Low income Hispanic families experience multiple barriers to accessing evidence-based information on Autism Spectrum Disorders (ASD). This study utilized a mixed-strategy intervention to create access to information in published bio-medical research articles on ASD by distilling the content into parent-friendly English- and Spanish-language ASD Science Briefs and presenting them to participants using two socially-oriented dissemination methods. There was a main effect for short-term knowledge gains associated with the Science Briefs but no effect for the dissemination method. After 5 months, participants reported utilizing the information learned and 90% wanted to read more Science Briefs. These preliminary findings highlight the potential benefits of distilling biomedical research articles on ASD into parent-friendly educational products for currently underserved Hispanic parents. PMID:26563948

Construction of an annotated corpus to support biomedical information extraction

PubMed Central

Thompson, Paul; Iqbal, Syed A; McNaught, John; Ananiadou, Sophia

2009-01-01

Background Information Extraction (IE) is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge document collections. As events are usually centred on verbs and nominalised verbs, understanding the syntactic and semantic behaviour of these words is highly important. Corpora annotated with information concerning this behaviour can constitute a valuable resource in the training of IE components and resources. Results We have defined a new scheme for annotating sentence-bound gene regulation events, centred on both verbs and nominalised verbs. For each event instance, all participants (arguments) in the same sentence are identified and assigned a semantic role from a rich set of 13 roles tailored to biomedical research articles, together with a biological concept type linked to the Gene Regulation Ontology. To our knowledge, our scheme is unique within the biomedical field in terms of the range of event arguments identified. Using the scheme, we have created the Gene Regulation Event Corpus (GREC), consisting of 240 MEDLINE abstracts, in which events relating to gene regulation and expression have been annotated by biologists. A novel method of evaluating various different facets of the annotation task showed that average inter-annotator agreement rates fall within the range of 66% - 90%. Conclusion The GREC is a unique resource within the biomedical field, in that it annotates not only core relationships between entities, but also a range of other important details about these relationships, e.g., location, temporal, manner and environmental conditions. As such, it is specifically designed to support bio-specific tool and resource development. It has already been used to acquire semantic frames for inclusion within the BioLexicon (a lexical, terminological resource to aid biomedical text mining). Initial experiments have also shown that the corpus may viably be used to train IE

The BioLexicon: a large-scale terminological resource for biomedical text mining

PubMed Central

2011-01-01

Background Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical

The BioLexicon: a large-scale terminological resource for biomedical text mining.

PubMed

Thompson, Paul; McNaught, John; Montemagni, Simonetta; Calzolari, Nicoletta; del Gratta, Riccardo; Lee, Vivian; Marchi, Simone; Monachini, Monica; Pezik, Piotr; Quochi, Valeria; Rupp, C J; Sasaki, Yutaka; Venturi, Giulia; Rebholz-Schuhmann, Dietrich; Ananiadou, Sophia

2011-10-12

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an

Expert Search Strategies: The Information Retrieval Practices of Healthcare Information Professionals.

PubMed

Russell-Rose, Tony; Chamberlain, Jon

2017-10-02

Healthcare information professionals play a key role in closing the knowledge gap between medical research and clinical practice. Their work involves meticulous searching of literature databases using complex search strategies that can consist of hundreds of keywords, operators, and ontology terms. This process is prone to error and can lead to inefficiency and bias if performed incorrectly. The aim of this study was to investigate the search behavior of healthcare information professionals, uncovering their needs, goals, and requirements for information retrieval systems. A survey was distributed to healthcare information professionals via professional association email discussion lists. It investigated the search tasks they undertake, their techniques for search strategy formulation, their approaches to evaluating search results, and their preferred functionality for searching library-style databases. The popular literature search system PubMed was then evaluated to determine the extent to which their needs were met. The 107 respondents indicated that their information retrieval process relied on the use of complex, repeatable, and transparent search strategies. On average it took 60 minutes to formulate a search strategy, with a search task taking 4 hours and consisting of 15 strategy lines. Respondents reviewed a median of 175 results per search task, far more than they would ideally like (100). The most desired features of a search system were merging search queries and combining search results. Healthcare information professionals routinely address some of the most challenging information retrieval problems of any profession. However, their needs are not fully supported by current literature search systems and there is demand for improved functionality, in particular regarding the development and management of search strategies. ©Tony Russell-Rose, Jon Chamberlain. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.10.2017.

Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

NASA Astrophysics Data System (ADS)

Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

2015-12-01

We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction

[Systems of biomedical information on the internet: bibliographic contents and electronic magazines].

PubMed

Belmonte, M

In this article we review two of the main Internet information services for seeking references to bibliography and journals, and the electronic publications on the Internet, with particular emphasis on those related to neurosciencs. The main indices of bibliography are: 1. MEDLINE. By definition, this is the bibliography database. It is an 'on line' version of the magazine with a smaller format, published weekly with the title pages and summaries of most of the biomedical journals. It is based on the Index Medicus, a bibliographic index (on paper) which annually collects references to the most important biomedical journals. 2. EMBASE (Excerpta Medica). It is a direct competitor to MEDLINE, although it has the disadvantage of lack of government subsidies and is privately financed only. This bibliographic database, produced by the publishers Elsevier of Holland, covers approximately 3,500 biomedical journals from 110 countries, and is particularly useful for articles on drugs and toxicology. 3. Current Contents. It publishes the index Current Contents, a classic in this field, much appreciated by scientists in all areas: medicine, social, technology, arts and humanities. At present, it is available in an on line version known as CCC (Current Contents Connect), accessible through the web, but only to subscribers. There is a growing tendency towards the publication of biomedical journals on the Internet. Its full development, if correctly carried out, will mean the opportunity to have the best information available and will result in great benefit to all those who are already using new information technology.

Passage-Based Bibliographic Coupling: An Inter-Article Similarity Measure for Biomedical Articles

PubMed Central

Liu, Rey-Long

2015-01-01

Biomedical literature is an essential source of biomedical evidence. To translate the evidence for biomedicine study, researchers often need to carefully read multiple articles about specific biomedical issues. These articles thus need to be highly related to each other. They should share similar core contents, including research goals, methods, and findings. However, given an article r, it is challenging for search engines to retrieve highly related articles for r. In this paper, we present a technique PBC (Passage-based Bibliographic Coupling) that estimates inter-article similarity by seamlessly integrating bibliographic coupling with the information collected from context passages around important out-link citations (references) in each article. Empirical evaluation shows that PBC can significantly improve the retrieval of those articles that biomedical experts believe to be highly related to specific articles about gene-disease associations. PBC can thus be used to improve search engines in retrieving the highly related articles for any given article r, even when r is cited by very few (or even no) articles. The contribution is essential for those researchers and text mining systems that aim at cross-validating the evidence about specific gene-disease associations. PMID:26440794

Passage-Based Bibliographic Coupling: An Inter-Article Similarity Measure for Biomedical Articles.

PubMed

Liu, Rey-Long

2015-01-01

Biomedical literature is an essential source of biomedical evidence. To translate the evidence for biomedicine study, researchers often need to carefully read multiple articles about specific biomedical issues. These articles thus need to be highly related to each other. They should share similar core contents, including research goals, methods, and findings. However, given an article r, it is challenging for search engines to retrieve highly related articles for r. In this paper, we present a technique PBC (Passage-based Bibliographic Coupling) that estimates inter-article similarity by seamlessly integrating bibliographic coupling with the information collected from context passages around important out-link citations (references) in each article. Empirical evaluation shows that PBC can significantly improve the retrieval of those articles that biomedical experts believe to be highly related to specific articles about gene-disease associations. PBC can thus be used to improve search engines in retrieving the highly related articles for any given article r, even when r is cited by very few (or even no) articles. The contribution is essential for those researchers and text mining systems that aim at cross-validating the evidence about specific gene-disease associations.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

PubMed

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

Management of information in distributed biomedical collaboratories.

PubMed

Keator, David B

2009-01-01

Organizing and annotating biomedical data in structured ways has gained much interest and focus in the last 30 years. Driven by decreases in digital storage costs and advances in genetics sequencing, imaging, electronic data collection, and microarray technologies, data is being collected at an alarming rate. The specialization of fields in biology and medicine demonstrates the need for somewhat different structures for storage and retrieval of data. For biologists, the need for structured information and integration across a number of domains drives development. For clinical researchers and hospitals, the need for a structured medical record accessible to, ideally, any medical practitioner who might require it during the course of research or patient treatment, patient confidentiality, and security are the driving developmental factors. Scientific data management systems generally consist of a few core services: a backend database system, a front-end graphical user interface, and an export/import mechanism or data interchange format to both get data into and out of the database and share data with collaborators. The chapter introduces some existing databases, distributed file systems, and interchange languages used within the biomedical research and clinical communities for scientific data management and exchange.

Patient-Centered Tools for Medication Information Search.

PubMed

Wilcox, Lauren; Feiner, Steven; Elhadad, Noémie; Vawdrey, David; Tran, Tran H

2014-05-20

Recent research focused on online health information seeking highlights a heavy reliance on general-purpose search engines. However, current general-purpose search interfaces do not necessarily provide adequate support for non-experts in identifying suitable sources of health information. Popular search engines have recently introduced search tools in their user interfaces for a range of topics. In this work, we explore how such tools can support non-expert, patient-centered health information search. Scoping the current work to medication-related search, we report on findings from a formative study focused on the design of patient-centered, medication-information search tools. Our study included qualitative interviews with patients, family members, and domain experts, as well as observations of their use of Remedy, a technology probe embodying a set of search tools. Post-operative cardiothoracic surgery patients and their visiting family members used the tools to find information about their hospital medications and were interviewed before and after their use. Domain experts conducted similar search tasks and provided qualitative feedback on their preferences and recommendations for designing these tools. Findings from our study suggest the importance of four valuation principles underlying our tools: credibility, readability, consumer perspective, and topical relevance.

Managing biomedical image metadata for search and retrieval of similar images.

PubMed

Korenblum, Daniel; Rubin, Daniel; Napel, Sandy; Rodriguez, Cesar; Beaulieu, Chris

2011-08-01

Radiology images are generally disconnected from the metadata describing their contents, such as imaging observations ("semantic" metadata), which are usually described in text reports that are not directly linked to the images. We developed a system, the Biomedical Image Metadata Manager (BIMM) to (1) address the problem of managing biomedical image metadata and (2) facilitate the retrieval of similar images using semantic feature metadata. Our approach allows radiologists, researchers, and students to take advantage of the vast and growing repositories of medical image data by explicitly linking images to their associated metadata in a relational database that is globally accessible through a Web application. BIMM receives input in the form of standard-based metadata files using Web service and parses and stores the metadata in a relational database allowing efficient data query and maintenance capabilities. Upon querying BIMM for images, 2D regions of interest (ROIs) stored as metadata are automatically rendered onto preview images included in search results. The system's "match observations" function retrieves images with similar ROIs based on specific semantic features describing imaging observation characteristics (IOCs). We demonstrate that the system, using IOCs alone, can accurately retrieve images with diagnoses matching the query images, and we evaluate its performance on a set of annotated liver lesion images. BIMM has several potential applications, e.g., computer-aided detection and diagnosis, content-based image retrieval, automating medical analysis protocols, and gathering population statistics like disease prevalences. The system provides a framework for decision support systems, potentially improving their diagnostic accuracy and selection of appropriate therapies.

A System for Information Management in BioMedical Studies—SIMBioMS

PubMed Central

Krestyaninova, Maria; Zarins, Andris; Viksna, Juris; Kurbatova, Natalja; Rucevskis, Peteris; Neogi, Sudeshna Guha; Gostev, Mike; Perheentupa, Teemu; Knuuttila, Juha; Barrett, Amy; Lappalainen, Ilkka; Rung, Johan; Podnieks, Karlis; Sarkans, Ugis; McCarthy, Mark I; Brazma, Alvis

2009-01-01

Summary: SIMBioMS is a web-based open source software system for managing data and information in biomedical studies. It provides a solution for the collection, storage, management and retrieval of information about research subjects and biomedical samples, as well as experimental data obtained using a range of high-throughput technologies, including gene expression, genotyping, proteomics and metabonomics. The system can easily be customized and has proven to be successful in several large-scale multi-site collaborative projects. It is compatible with emerging functional genomics data standards and provides data import and export in accepted standard formats. Protocols for transferring data to durable archives at the European Bioinformatics Institute have been implemented. Availability: The source code, documentation and initialization scripts are available at http://simbioms.org. Contact: support@simbioms.org; mariak@ebi.ac.uk PMID:19633095

Figure Text Extraction in Biomedical Literature

PubMed Central

Kim, Daehyun; Yu, Hong

2011-01-01

Background Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. Methodology We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. Results/Conclusions The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19

Figure text extraction in biomedical literature.

PubMed

Kim, Daehyun; Yu, Hong

2011-01-13

Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for text

Patient-Centered Tools for Medication Information Search

PubMed Central

Wilcox, Lauren; Feiner, Steven; Elhadad, Noémie; Vawdrey, David; Tran, Tran H.

2016-01-01

Recent research focused on online health information seeking highlights a heavy reliance on general-purpose search engines. However, current general-purpose search interfaces do not necessarily provide adequate support for non-experts in identifying suitable sources of health information. Popular search engines have recently introduced search tools in their user interfaces for a range of topics. In this work, we explore how such tools can support non-expert, patient-centered health information search. Scoping the current work to medication-related search, we report on findings from a formative study focused on the design of patient-centered, medication-information search tools. Our study included qualitative interviews with patients, family members, and domain experts, as well as observations of their use of Remedy, a technology probe embodying a set of search tools. Post-operative cardiothoracic surgery patients and their visiting family members used the tools to find information about their hospital medications and were interviewed before and after their use. Domain experts conducted similar search tasks and provided qualitative feedback on their preferences and recommendations for designing these tools. Findings from our study suggest the importance of four valuation principles underlying our tools: credibility, readability, consumer perspective, and topical relevance. PMID:28163972

Strategies for Disseminating Information on Biomedical Research on Autism to Hispanic Parents

ERIC Educational Resources Information Center

Lajonchere, Clara M.; Wheeler, Barbara Y.; Valente, Thomas W.; Kreutzer, Cary; Munson, Aron; Narayanan, Shrikanth; Kazemzadeh, Abe; Cruz, Roxana; Martinez, Irene; Schrager, Sheree M.; Schweitzer, Lisa; Chklovski, Tara; Hwang, Darryl

2016-01-01

Low income Hispanic families experience multiple barriers to accessing evidence-based information on Autism Spectrum Disorders (ASD). This study utilized a mixed-strategy intervention to create access to information in published bio-medical research articles on ASD by distilling the content into parent-friendly English- and Spanish-language ASD…

How to Search, Write, Prepare and Publish the Scientific Papers in the Biomedical Journals

PubMed Central

Masic, Izet

2011-01-01

This article describes the methodology of preparation, writing and publishing scientific papers in biomedical journals. given is a concise overview of the concept and structure of the System of biomedical scientific and technical information and the way of biomedical literature retreival from worldwide biomedical databases. Described are the scientific and professional medical journals that are currently published in Bosnia and Herzegovina. Also, given is the comparative review on the number and structure of papers published in indexed journals in Bosnia and Herzegovina, which are listed in the Medline database. Analyzed are three B&H journals indexed in MEDLINE database: Medical Archives (Medicinski Arhiv), Bosnian Journal of Basic Medical Sciences and Medical Gazette (Medicinki Glasnik) in 2010. The largest number of original papers was published in the Medical Archives. There is a statistically significant difference in the number of papers published by local authors in relation to international journals in favor of the Medical Archives. True, the Journal Bosnian Journal of Basic Medical Sciences does not categorize the articles and we could not make comparisons. Journal Medical Archives and Bosnian Journal of Basic Medical Sciences by percentage published the largest number of articles by authors from Sarajevo and Tuzla, the two oldest and largest university medical centers in Bosnia and Herzegovina. The author believes that it is necessary to make qualitative changes in the reception and reviewing of papers for publication in biomedical journals published in Bosnia and Herzegovina which should be the responsibility of the separate scientific authority/ committee composed of experts in the field of medicine at the state level. PMID:23572850

Semantic similarity measures in the biomedical domain by leveraging a web search engine.

PubMed

Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching

2013-07-01

Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

Biomedical Applications of NASA Science and Technology

NASA Technical Reports Server (NTRS)

Brown, James N., Jr.

1968-01-01

During the period 15 September 1968 to 14 December 1968, the NASA supported Biomedical Application Team at the Research Triangle Institute has identified 6 new problems, performed significant activities on 15 of the active problems identified previously, performed 5 computer searches of the NASA aerospace literature, and maintained one current awareness search. As a partial result of these activities, one technology transfer was accomplished. As a part of continuing problem review, 13 problems were classified inactive. Activities during the quarter involved all phases of team activity with respect to biomedical problems. As has been observed in preceding years, it has been exceedingly difficult to arrange meetings with medical investigators during the fourth quarter of the calendar year. This is a result of a combination of factors. Teaching requirements, submission of grant applications and holidays are the most significant factors involved. As a result, the numbers of new problems identified and of transfers and potential transfers are relatively low during this quarter. Most of our activities have thus been directed toward obtaining information related to problems already identified. Consequently, during the next quarter we will follow up on these activities with the expectation that transfers will be accomplished on a number of them. In addition, the normal availability of researchers to the team is expected to be restored during this quarter, permitting an increase in new problem identification activities as well as follow-up with other researchers on old problems. Another activity scheduled for the next quarter is consultation with several interested biomedical equipment manufacturers to explore means of effective interaction between the Biomedical Application Team and these companies.

Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

PubMed

Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

2013-01-01

Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

Recommending images of user interests from the biomedical literature

NASA Astrophysics Data System (ADS)

Clukey, Steven; Xu, Songhua

2013-03-01

Every year hundreds of thousands of biomedical images are published in journals and conferences. Consequently, finding images relevant to one's interests becomes an ever daunting task. This vast amount of literature creates a need for intelligent and easy-to-use tools that can help researchers effectively navigate through the content corpus and conveniently locate materials of their interests. Traditionally, literature search tools allow users to query content using topic keywords. However, manual query composition is often time and energy consuming. A better system would be one that can automatically deliver relevant content to a researcher without having the end user manually manifest one's search intent and interests via search queries. Such a computer-aided assistance for information access can be provided by a system that first determines a researcher's interests automatically and then recommends images relevant to the person's interests accordingly. The technology can greatly improve a researcher's ability to stay up to date in their fields of study by allowing them to efficiently browse images and documents matching their needs and interests among the vast amount of the biomedical literature. A prototype system implementation of the technology can be accessed via http://www.smartdataware.com.

GeneView: a comprehensive semantic search engine for PubMed.

PubMed

Thomas, Philippe; Starlinger, Johannes; Vowinkel, Alexander; Arzt, Sebastian; Leser, Ulf

2012-07-01

Research results are primarily published in scientific literature and curation efforts cannot keep up with the rapid growth of published literature. The plethora of knowledge remains hidden in large text repositories like MEDLINE. Consequently, life scientists have to spend a great amount of time searching for specific information. The enormous ambiguity among most names of biomedical objects such as genes, chemicals and diseases often produces too large and unspecific search results. We present GeneView, a semantic search engine for biomedical knowledge. GeneView is built upon a comprehensively annotated version of PubMed abstracts and openly available PubMed Central full texts. This semi-structured representation of biomedical texts enables a number of features extending classical search engines. For instance, users may search for entities using unique database identifiers or they may rank documents by the number of specific mentions they contain. Annotation is performed by a multitude of state-of-the-art text-mining tools for recognizing mentions from 10 entity classes and for identifying protein-protein interactions. GeneView currently contains annotations for >194 million entities from 10 classes for ∼21 million citations with 271,000 full text bodies. GeneView can be searched at http://bc3.informatik.hu-berlin.de/.

International biomedical law in search for its normative status.

PubMed

Krajewska, Atina

2012-01-01

The broad and multifaceted problem of global health law and global health governance has been attracting increasing attention in the last few decades. The global community has failed to establish international legal regime that deals comprehensively with the 'technological revolution'. The latter has posed complex questions to regions of the world with widely differing cultural perspectives. At the same time, an increasing number of governmental and non-state actors have become significantly involved in the sector. They use legal, political, and other forms of decision-making that result in regulatory instruments of contrasting normative status. Law created in this heterogeneous environment has been said to be fragmented, inconsistent, and exacerbating uncertainties. Therefore, claims have been made that a centralised and institutionalised system would help address the problems of transparency, legitimacy and efficiency. Nevertheless, little scholarly consideration is paid to the normative status of international biomedical law. This paper explores whether formalisation and "constitutionalisation" of biomedical law are indeed inevitable for its establishment as a separate regulatory regime. It does so by analysing the proliferation of biomedical law in light of two the theory of fragmentation and the theory of global legal pluralism. Investigating the problem in this way helps determine the theoretical framework and methodology of future studies of biomedical law at the international level. This in turn should help its future development in a more consistent and harmonised manner.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature.

PubMed

Perez-Rey, David; Jimenez-Castellanos, Ana; Garcia-Remesal, Miguel; Crespo, Jose; Maojo, Victor

2012-04-05

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset

Method for detecting core malware sites related to biomedical information systems.

PubMed

Kim, Dohoon; Choi, Donghee; Jin, Jonghyun

2015-01-01

Most advanced persistent threat attacks target web users through malicious code within landing (exploit) or distribution sites. There is an urgent need to block the affected websites. Attacks on biomedical information systems are no exception to this issue. In this paper, we present a method for locating malicious websites that attempt to attack biomedical information systems. Our approach uses malicious code crawling to rearrange websites in the order of their risk index by analyzing the centrality between malware sites and proactively eliminates the root of these sites by finding the core-hub node, thereby reducing unnecessary security policies. In particular, we dynamically estimate the risk index of the affected websites by analyzing various centrality measures and converting them into a single quantified vector. On average, the proactive elimination of core malicious websites results in an average improvement in zero-day attack detection of more than 20%.

Method for Detecting Core Malware Sites Related to Biomedical Information Systems

PubMed Central

Kim, Dohoon; Choi, Donghee; Jin, Jonghyun

2015-01-01

Most advanced persistent threat attacks target web users through malicious code within landing (exploit) or distribution sites. There is an urgent need to block the affected websites. Attacks on biomedical information systems are no exception to this issue. In this paper, we present a method for locating malicious websites that attempt to attack biomedical information systems. Our approach uses malicious code crawling to rearrange websites in the order of their risk index by analyzing the centrality between malware sites and proactively eliminates the root of these sites by finding the core-hub node, thereby reducing unnecessary security policies. In particular, we dynamically estimate the risk index of the affected websites by analyzing various centrality measures and converting them into a single quantified vector. On average, the proactive elimination of core malicious websites results in an average improvement in zero-day attack detection of more than 20%. PMID:25821511

When is Information Sufficient for Action Search with Unreliable Yet Informative Intelligence

DTIC Science & Technology

2016-03-30

information: http://pubsonline.informs.org When Is Information Sufficient for Action? Search with Unreliable yet Informative Intelligence Michael Atkinson... Search with Unreliable yet Informative Intelligence. Operations Research Published online in Articles in Advance 30 Mar 2016 . http://dx.doi.org/10.1287...print) � ISSN 1526-5463 (online) http://dx.doi.org/10.1287/opre.2016.1488 © 2016 INFORMS When Is Information Sufficient for Action? Search with

Sexual information seeking on web search engines.

PubMed

Spink, Amanda; Koricich, Andrew; Jansen, B J; Cole, Charles

2004-02-01

Sexual information seeking is an important element within human information behavior. Seeking sexually related information on the Internet takes many forms and channels, including chat rooms discussions, accessing Websites or searching Web search engines for sexual materials. The study of sexual Web queries provides insight into sexually-related information-seeking behavior, of value to Web users and providers alike. We qualitatively analyzed queries from logs of 1,025,910 Alta Vista and AlltheWeb.com Web user queries from 2001. We compared the differences in sexually-related Web searching between Alta Vista and AlltheWeb.com users. Differences were found in session duration, query outcomes, and search term choices. Implications of the findings for sexual information seeking are discussed.

Text Mining in Biomedical Domain with Emphasis on Document Clustering

PubMed Central

2017-01-01

Objectives With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. Methods This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Results Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Conclusions Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise. PMID:28875048

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

PubMed

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

Biomedical data mining in clinical routine: expanding the impact of hospital information systems.

PubMed

Müller, Marcel; Markó, Kornel; Daumke, Philipp; Paetzold, Jan; Roesner, Arnold; Klar, Rüdiger

2007-01-01

In this paper we want to describe how the promising technology of biomedical data mining can improve the use of hospital information systems: a large set of unstructured, narrative clinical data from a dermatological university hospital like discharge letters or other dermatological reports were processed through a morpho-semantic text retrieval engine ("MorphoSaurus") and integrated with other clinical data using a web-based interface and brought into daily clinical routine. The user evaluation showed a very high user acceptance - this system seems to meet the clinicians' requirements for a vertical data mining in the electronic patient records. What emerges is the need for integration of biomedical data mining into hospital information systems for clinical, scientific, educational and economic reasons.

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

What is biomedical informatics?

PubMed Central

Bernstam, Elmer V.; Smith, Jack W.; Johnson, Todd R.

2009-01-01

Biomedical informatics lacks a clear and theoretically grounded definition. Many proposed definitions focus on data, information, and knowledge, but do not provide an adequate definition of these terms. Leveraging insights from the philosophy of information, we define informatics as the science of information, where information is data plus meaning. Biomedical informatics is the science of information as applied to or studied in the context of biomedicine. Defining the object of study of informatics as data plus meaning clearly distinguishes the field from related fields, such as computer science, statistics and biomedicine, which have different objects of study. The emphasis on data plus meaning also suggests that biomedical informatics problems tend to be difficult when they deal with concepts that are hard to capture using formal, computational definitions. In other words, problems where meaning must be considered are more difficult than problems where manipulating data without regard for meaning is sufficient. Furthermore, the definition implies that informatics research, teaching, and service should focus on biomedical information as data plus meaning rather than only computer applications in biomedicine. PMID:19683067

Biomedical question answering using semantic relations.

PubMed

Hristovski, Dimitar; Dinevski, Dejan; Kastrin, Andrej; Rindflesch, Thomas C

2015-01-16

The proliferation of the scientific literature in the field of biomedicine makes it difficult to keep abreast of current knowledge, even for domain experts. While general Web search engines and specialized information retrieval (IR) systems have made important strides in recent decades, the problem of accurate knowledge extraction from the biomedical literature is far from solved. Classical IR systems usually return a list of documents that have to be read by the user to extract relevant information. This tedious and time-consuming work can be lessened with automatic Question Answering (QA) systems, which aim to provide users with direct and precise answers to their questions. In this work we propose a novel methodology for QA based on semantic relations extracted from the biomedical literature. We extracted semantic relations with the SemRep natural language processing system from 122,421,765 sentences, which came from 21,014,382 MEDLINE citations (i.e., the complete MEDLINE distribution up to the end of 2012). A total of 58,879,300 semantic relation instances were extracted and organized in a relational database. The QA process is implemented as a search in this database, which is accessed through a Web-based application, called SemBT (available at http://sembt.mf.uni-lj.si ). We conducted an extensive evaluation of the proposed methodology in order to estimate the accuracy of extracting a particular semantic relation from a particular sentence. Evaluation was performed by 80 domain experts. In total 7,510 semantic relation instances belonging to 2,675 distinct relations were evaluated 12,083 times. The instances were evaluated as correct 8,228 times (68%). In this work we propose an innovative methodology for biomedical QA. The system is implemented as a Web-based application that is able to provide precise answers to a wide range of questions. A typical question is answered within a few seconds. The tool has some extensions that make it especially useful for

Information Diversity in Web Search

ERIC Educational Resources Information Center

Liu, Jiahui

2009-01-01

The web is a rich and diverse information source with incredible amounts of information about all kinds of subjects in various forms. This information source affords great opportunity to build systems that support users in their work and everyday lives. To help users explore information on the web, web search systems should find information that…

Semantic biomedical resource discovery: a Natural Language Processing framework.

PubMed

Sfakianaki, Pepi; Koumakis, Lefteris; Sfakianakis, Stelios; Iatraki, Galatia; Zacharioudakis, Giorgos; Graf, Norbert; Marias, Kostas; Tsiknakis, Manolis

2015-09-30

A plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language. A Natural Language Processing engine which can "translate" free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at ( http://calchas.ics.forth.gr/ ). For our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either

Online Information Search Performance and Search Strategies in a Health Problem-Solving Scenario.

PubMed

Sharit, Joseph; Taha, Jessica; Berkowsky, Ronald W; Profita, Halley; Czaja, Sara J

2015-01-01

Although access to Internet health information can be beneficial, solving complex health-related problems online is challenging for many individuals. In this study, we investigated the performance of a sample of 60 adults ages 18 to 85 years in using the Internet to resolve a relatively complex health information problem. The impact of age, Internet experience, and cognitive abilities on measures of search time, amount of search, and search accuracy was examined, and a model of Internet information seeking was developed to guide the characterization of participants' search strategies. Internet experience was found to have no impact on performance measures. Older participants exhibited longer search times and lower amounts of search but similar search accuracy performance as their younger counterparts. Overall, greater search accuracy was related to an increased amount of search but not to increased search duration and was primarily attributable to higher cognitive abilities, such as processing speed, reasoning ability, and executive function. There was a tendency for those who were younger, had greater Internet experience, and had higher cognitive abilities to use a bottom-up (i.e., analytic) search strategy, although use of a top-down (i.e., browsing) strategy was not necessarily unsuccessful. Implications of the findings for future studies and design interventions are discussed.

Online Information Search Performance and Search Strategies in a Health Problem-Solving Scenario

PubMed Central

Sharit, Joseph; Taha, Jessica; Berkowsky, Ronald W.; Profita, Halley; Czaja, Sara J.

2017-01-01

Although access to Internet health information can be beneficial, solving complex health-related problems online is challenging for many individuals. In this study, we investigated the performance of a sample of 60 adults ages 18 to 85 years in using the Internet to resolve a relatively complex health information problem. The impact of age, Internet experience, and cognitive abilities on measures of search time, amount of search, and search accuracy was examined, and a model of Internet information seeking was developed to guide the characterization of participants’ search strategies. Internet experience was found to have no impact on performance measures. Older participants exhibited longer search times and lower amounts of search but similar search accuracy performance as their younger counterparts. Overall, greater search accuracy was related to an increased amount of search but not to increased search duration and was primarily attributable to higher cognitive abilities, such as processing speed, reasoning ability, and executive function. There was a tendency for those who were younger, had greater Internet experience, and had higher cognitive abilities to use a bottom-up (i.e., analytic) search strategy, although use of a top-down (i.e., browsing) strategy was not necessarily unsuccessful. Implications of the findings for future studies and design interventions are discussed. PMID:29056885

CNN-based ranking for biomedical entity normalization.

PubMed

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

Implementation and management of a biomedical observation dictionary in a large healthcare information system.

PubMed

Vandenbussche, Pierre-Yves; Cormont, Sylvie; André, Christophe; Daniel, Christel; Delahousse, Jean; Charlet, Jean; Lepage, Eric

2013-01-01

This study shows the evolution of a biomedical observation dictionary within the Assistance Publique Hôpitaux Paris (AP-HP), the largest European university hospital group. The different steps are detailed as follows: the dictionary creation, the mapping to logical observation identifier names and codes (LOINC), the integration into a multiterminological management platform and, finally, the implementation in the health information system. AP-HP decided to create a biomedical observation dictionary named AnaBio, to map it to LOINC and to maintain the mapping. A management platform based on methods used for knowledge engineering has been put in place. It aims at integrating AnaBio within the health information system and improving both the quality and stability of the dictionary. This new management platform is now active in AP-HP. The AnaBio dictionary is shared by 120 laboratories and currently includes 50 000 codes. The mapping implementation to LOINC reaches 40% of the AnaBio entries and uses 26% of LOINC records. The results of our work validate the choice made to develop a local dictionary aligned with LOINC. This work constitutes a first step towards a wider use of the platform. The next step will support the entire biomedical production chain, from the clinician prescription, through laboratory tests tracking in the laboratory information system to the communication of results and the use for decision support and biomedical research. In addition, the increase in the mapping implementation to LOINC ensures the interoperability allowing communication with other international health institutions.

Implementation and management of a biomedical observation dictionary in a large healthcare information system

PubMed Central

Vandenbussche, Pierre-Yves; Cormont, Sylvie; André, Christophe; Daniel, Christel; Delahousse, Jean; Charlet, Jean; Lepage, Eric

2013-01-01

Objective This study shows the evolution of a biomedical observation dictionary within the Assistance Publique Hôpitaux Paris (AP-HP), the largest European university hospital group. The different steps are detailed as follows: the dictionary creation, the mapping to logical observation identifier names and codes (LOINC), the integration into a multiterminological management platform and, finally, the implementation in the health information system. Methods AP-HP decided to create a biomedical observation dictionary named AnaBio, to map it to LOINC and to maintain the mapping. A management platform based on methods used for knowledge engineering has been put in place. It aims at integrating AnaBio within the health information system and improving both the quality and stability of the dictionary. Results This new management platform is now active in AP-HP. The AnaBio dictionary is shared by 120 laboratories and currently includes 50 000 codes. The mapping implementation to LOINC reaches 40% of the AnaBio entries and uses 26% of LOINC records. The results of our work validate the choice made to develop a local dictionary aligned with LOINC. Discussion and Conclusions This work constitutes a first step towards a wider use of the platform. The next step will support the entire biomedical production chain, from the clinician prescription, through laboratory tests tracking in the laboratory information system to the communication of results and the use for decision support and biomedical research. In addition, the increase in the mapping implementation to LOINC ensures the interoperability allowing communication with other international health institutions. PMID:23635601

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos

PubMed Central

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-01-01

Objective Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today’s keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users’ information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. Materials and Methods The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively. Results The authors produced a prototype implementation of the proposed system, which is publicly accessible at https://patentq.njit.edu/oer. To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Conclusion Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

PubMed

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-04-01

Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable

PhysiomeSpace: digital library service for biomedical data

PubMed Central

Testi, Debora; Quadrani, Paolo; Viceconti, Marco

2010-01-01

Every research laboratory has a wealth of biomedical data locked up, which, if shared with other experts, could dramatically improve biomedical and healthcare research. With the PhysiomeSpace service, it is now possible with a few clicks to share with selected users biomedical data in an easy, controlled and safe way. The digital library service is managed using a client–server approach. The client application is used to import, fuse and enrich the data information according to the PhysiomeSpace resource ontology and upload/download the data to the library. The server services are hosted on the Biomed Town community portal, where through a web interface, the user can complete the metadata curation and share and/or publish the data resources. A search service capitalizes on the domain ontology and on the enrichment of metadata for each resource, providing a powerful discovery environment. Once the users have found the data resources they are interested in, they can add them to their basket, following a metaphor popular in e-commerce web sites. When all the necessary resources have been selected, the user can download the basket contents into the client application. The digital library service is now in beta and open to the biomedical research community. PMID:20478910

PhysiomeSpace: digital library service for biomedical data.

PubMed

Testi, Debora; Quadrani, Paolo; Viceconti, Marco

2010-06-28

Every research laboratory has a wealth of biomedical data locked up, which, if shared with other experts, could dramatically improve biomedical and healthcare research. With the PhysiomeSpace service, it is now possible with a few clicks to share with selected users biomedical data in an easy, controlled and safe way. The digital library service is managed using a client-server approach. The client application is used to import, fuse and enrich the data information according to the PhysiomeSpace resource ontology and upload/download the data to the library. The server services are hosted on the Biomed Town community portal, where through a web interface, the user can complete the metadata curation and share and/or publish the data resources. A search service capitalizes on the domain ontology and on the enrichment of metadata for each resource, providing a powerful discovery environment. Once the users have found the data resources they are interested in, they can add them to their basket, following a metaphor popular in e-commerce web sites. When all the necessary resources have been selected, the user can download the basket contents into the client application. The digital library service is now in beta and open to the biomedical research community.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

PubMed Central

2012-01-01

Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has

The Influence of Biomedical Information and Childhood History on Sentencing.

PubMed

Kim, JongHan; Boytos, Abby; Seong, Yoori; Park, Kwangbai

2015-01-01

A recent trend in court is for defense attorneys to introduce brain scans and other forms of biomedical information (BI) into criminal trials as mitigating evidence. The present study investigates how BI, when considered in combination with a defendant's childhood information (CI), can influence the length of a defendant's sentence. We hypothesized that certain combinations of BI and CI result in shorter sentences because they suggest that the defendant poses less of a threat to society. Participants were asked to read accounts of the trial of a murder suspect and, based on the information therein, recommend a sentence as if they were the judge. The defendant was diagnosed with psychopathy, but biomedical information regarding that diagnosis was included or excluded depending on the BI condition. The defendant was further described as growing up in either a loving or abusive family. The results showed that, if BI was present in the trial account, the defendant from an abusive family was perceived as less of a threat to society and received a shorter recommended sentence than if the defendant had been from a loving family. If BI was absent from the account, the pattern was reversed: the defendant from a loving family was perceived as less of a threat to society and received a shorter recommended sentence than if he had been from an abusive family. Implications for the use of BI and CI in court trials are discussed, as well as their relationship to free will and the function of punishment as retribution and utility. Copyright © 2015 John Wiley & Sons, Ltd.

The Effects of Preference for Information on Consumers’ Online Health Information Search Behavior

PubMed Central

2013-01-01

Background Preference for information is a personality trait that affects people’s tendency to seek information in health-related situations. Prior studies have focused primarily on investigating its impact on patient-provider communication and on the implications for designing information interventions that prepare patients for medical procedures. Few studies have examined its impact on general consumers’ interactions with Web-based search engines for health information or the implications for designing more effective health information search systems. Objective This study intends to fill this gap by investigating the impact of preference for information on the search behavior of general consumers seeking health information, their perceptions of search tasks (representing information needs), and user experience with search systems. Methods Forty general consumers who had previously searched for health information online participated in the study in our usability lab. Preference for information was measured using Miller’s Monitor-Blunter Style Scale (MBSS) and the Krantz Health Opinion Survey-Information Scale (KHOS-I). Each participant completed four simulated health information search tasks: two look-up (fact-finding) and two exploratory. Their behaviors while interacting with the search systems were automatically logged and ratings of their perceptions of tasks and user experience with the systems were collected using Likert-scale questionnaires. Results The MBSS showed low reliability with the participants (Monitoring subscale: Cronbach alpha=.53; Blunting subscale: Cronbach alpha=.35). Thus, no further analyses were performed based on the scale. KHOS-I had sufficient reliability (Cronbach alpha=.77). Participants were classified into low- and high-preference groups based on their KHOS-I scores. The high-preference group submitted significantly shorter queries when completing the look-up tasks (P=.02). The high-preference group made a significantly higher

The effects of preference for information on consumers' online health information search behavior.

PubMed

Zhang, Yan

2013-11-26

Preference for information is a personality trait that affects people's tendency to seek information in health-related situations. Prior studies have focused primarily on investigating its impact on patient-provider communication and on the implications for designing information interventions that prepare patients for medical procedures. Few studies have examined its impact on general consumers' interactions with Web-based search engines for health information or the implications for designing more effective health information search systems. This study intends to fill this gap by investigating the impact of preference for information on the search behavior of general consumers seeking health information, their perceptions of search tasks (representing information needs), and user experience with search systems. Forty general consumers who had previously searched for health information online participated in the study in our usability lab. Preference for information was measured using Miller's Monitor-Blunter Style Scale (MBSS) and the Krantz Health Opinion Survey-Information Scale (KHOS-I). Each participant completed four simulated health information search tasks: two look-up (fact-finding) and two exploratory. Their behaviors while interacting with the search systems were automatically logged and ratings of their perceptions of tasks and user experience with the systems were collected using Likert-scale questionnaires. The MBSS showed low reliability with the participants (Monitoring subscale: Cronbach alpha=.53; Blunting subscale: Cronbach alpha=.35). Thus, no further analyses were performed based on the scale. KHOS-I had sufficient reliability (Cronbach alpha=.77). Participants were classified into low- and high-preference groups based on their KHOS-I scores. The high-preference group submitted significantly shorter queries when completing the look-up tasks (P=.02). The high-preference group made a significantly higher percentage of parallel movements in query

Self Esteem, Information Search and Problem Solving Efficiency.

DTIC Science & Technology

1979-05-01

Weiss (1977, 1978) has shown that low self esteem workers are more likely to model the role behaviors and work values of superiors than are high self ...task where search is functional. Results showed that, as expected, low self esteem subjects searched for more information, search was functional and low ...situation. He has also argued that high self esteem individuals search for less information on problem solving tasks and are therefore less likely to

Specialized medical search-engines are no better than general search-engines in sourcing consumer information about androgen deficiency.

PubMed

Ilic, D; Bessell, T L; Silagy, C A; Green, S

2003-03-01

The Internet provides consumers with access to online health information; however, identifying relevant and valid information can be problematic. Our objectives were firstly to investigate the efficiency of search-engines, and then to assess the quality of online information pertaining to androgen deficiency in the ageing male (ADAM). Keyword searches were performed on nine search-engines (four general and five medical) to identify website information regarding ADAM. Search-engine efficiency was compared by percentage of relevant websites obtained via each search-engine. The quality of information published on each website was assessed using the DISCERN rating tool. Of 4927 websites searched, 47 (1.44%) and 10 (0.60%) relevant websites were identified by general and medical search-engines respectively. The overall quality of online information on ADAM was poor. The quality of websites retrieved using medical search-engines did not differ significantly from those retrieved by general search-engines. Despite the poor quality of online information relating to ADAM, it is evident that medical search-engines are no better than general search-engines in sourcing consumer information relevant to ADAM.

Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review.

PubMed

Guo, Yufan; Silins, Ilona; Stenius, Ulla; Korhonen, Anna

2013-06-01

Techniques that are capable of automatically analyzing the information structure of scientific articles could be highly useful for improving information access to biomedical literature. However, most existing approaches rely on supervised machine learning (ML) and substantial labeled data that are expensive to develop and apply to different sub-fields of biomedicine. Recent research shows that minimal supervision is sufficient for fairly accurate information structure analysis of biomedical abstracts. However, is it realistic for full articles given their high linguistic and informational complexity? We introduce and release a novel corpus of 50 biomedical articles annotated according to the Argumentative Zoning (AZ) scheme, and investigate active learning with one of the most widely used ML models-Support Vector Machines (SVM)-on this corpus. Additionally, we introduce two novel applications that use AZ to support real-life literature review in biomedicine via question answering and summarization. We show that active learning with SVM trained on 500 labeled sentences (6% of the corpus) performs surprisingly well with the accuracy of 82%, just 2% lower than fully supervised learning. In our question answering task, biomedical researchers find relevant information significantly faster from AZ-annotated than unannotated articles. In the summarization task, sentences extracted from particular zones are significantly more similar to gold standard summaries than those extracted from particular sections of full articles. These results demonstrate that active learning of full articles' information structure is indeed realistic and the accuracy is high enough to support real-life literature review in biomedicine. The annotated corpus, our AZ classifier and the two novel applications are available at http://www.cl.cam.ac.uk/yg244/12bioinfo.html

Environmental/Biomedical Terminology Index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huffstetler, J.K.; Dailey, N.S.; Rickert, L.W.

1976-12-01

The Information Center Complex (ICC), a centrally administered group of information centers, provides information support to environmental and biomedical research groups and others within and outside Oak Ridge National Laboratory. In-house data base building and development of specialized document collections are important elements of the ongoing activities of these centers. ICC groups must be concerned with language which will adequately classify and insure retrievability of document records. Language control problems are compounded when the complexity of modern scientific problem solving demands an interdisciplinary approach. Although there are several word lists, indexes, and thesauri specific to various scientific disciplines usually groupedmore » as Environmental Sciences, no single generally recognized authority can be used as a guide to the terminology of all environmental science. If biomedical terminology for the description of research on environmental effects is also needed, the problem becomes even more complex. The building of a word list which can be used as a general guide to the environmental/biomedical sciences has been a continuing activity of the Information Center Complex. This activity resulted in the publication of the Environmental Biomedical Terminology Index (EBTI).« less

Combinatorial Fusion Analysis for Meta Search Information Retrieval

NASA Astrophysics Data System (ADS)

Hsu, D. Frank; Taksa, Isak

Leading commercial search engines are built as single event systems. In response to a particular search query, the search engine returns a single list of ranked search results. To find more relevant results the user must frequently try several other search engines. A meta search engine was developed to enhance the process of multi-engine querying. The meta search engine queries several engines at the same time and fuses individual engine results into a single search results list. The fusion of multiple search results has been shown (mostly experimentally) to be highly effective. However, the question of why and how the fusion should be done still remains largely unanswered. In this chapter, we utilize the combinatorial fusion analysis proposed by Hsu et al. to analyze combination and fusion of multiple sources of information. A rank/score function is used in the design and analysis of our framework. The framework provides a better understanding of the fusion phenomenon in information retrieval. For example, to improve the performance of the combined multiple scoring systems, it is necessary that each of the individual scoring systems has relatively high performance and the individual scoring systems are diverse. Additionally, we illustrate various applications of the framework using two examples from the information retrieval domain.

How to locate & hire clinical/biomedical engineers, supervisors, managers & biomedical equipment technicians.

PubMed

Pacela, A F; Brush, L C

1993-01-01

This article has described the process and the resources available for locating and hiring clinical/biomedical engineers, supervisors, managers, and biomedical equipment technicians. First, the employer must determine the qualifications for the position, including job titles, descriptions, pay scales, and certification requirements. Next, the employer must find qualified applicants. The most common way to do this is to use "outside" contacts, such as help-wanted advertising, specialized job placement agencies, schools and colleges, military resources, regional biomedical societies, and nationwide societies. An "inside" search involves limited internal advertising of the position and using personal referrals for candidates. Finally, the employer must screen the applicants. The position description is the obvious first step in this process, but there are other pre-screening techniques, such as employment testing. Interviewing is the most common way to hire for job positions, but the interviewer needs to know about the position and ask the right questions. Post-interview screening is a final step to help determine the best job-person match.

A scoping review of competencies for scientific editors of biomedical journals.

PubMed

Galipeau, James; Barbour, Virginia; Baskin, Patricia; Bell-Syer, Sally; Cobey, Kelly; Cumpston, Miranda; Deeks, Jon; Garner, Paul; MacLehose, Harriet; Shamseer, Larissa; Straus, Sharon; Tugwell, Peter; Wager, Elizabeth; Winker, Margaret; Moher, David

2016-02-02

Biomedical journals are the main route for disseminating the results of health-related research. Despite this, their editors operate largely without formal training or certification. To our knowledge, no body of literature systematically identifying core competencies for scientific editors of biomedical journals exists. Therefore, we aimed to conduct a scoping review to determine what is known on the competency requirements for scientific editors of biomedical journals. We searched the MEDLINE®, Cochrane Library, Embase®, CINAHL, PsycINFO, and ERIC databases (from inception to November 2014) and conducted a grey literature search for research and non-research articles with competency-related statements (i.e. competencies, knowledge, skills, behaviors, and tasks) pertaining to the role of scientific editors of peer-reviewed health-related journals. We also conducted an environmental scan, searched the results of a previous environmental scan, and searched the websites of existing networks, major biomedical journal publishers, and organizations that offer resources for editors. A total of 225 full-text publications were included, 25 of which were research articles. We extracted a total of 1,566 statements possibly related to core competencies for scientific editors of biomedical journals from these publications. We then collated overlapping or duplicate statements which produced a list of 203 unique statements. Finally, we grouped these statements into seven emergent themes: (1) dealing with authors, (2) dealing with peer reviewers, (3) journal publishing, (4) journal promotion, (5) editing, (6) ethics and integrity, and (7) qualities and characteristics of editors. To our knowledge, this scoping review is the first attempt to systematically identify possible competencies of editors. Limitations are that (1) we may not have captured all aspects of a biomedical editor's work in our searches, (2) removing redundant and overlapping items may have led to the

How social information affects information search and choice in probabilistic inferences.

PubMed

Puskaric, Marin; von Helversen, Bettina; Rieskamp, Jörg

2018-01-01

When making decisions, people are often exposed to relevant information stemming from qualitatively different sources. For instance, when making a choice between two alternatives people can rely on the advice of other people (i.e., social information) or search for factual information about the alternatives (i.e., non-social information). Prior research in categorization has shown that social information is given special attention when both social and non-social information is available, even when the social information has no additional informational value. The goal of the current work is to investigate whether framing information as social or non-social also influences information search and choice in probabilistic inferences. In a first study, we found that framing cues (i.e., the information used to make a decision) with medium validity as social increased the probability that they were searched for compared to a task where the same cues were framed as non-social information, but did not change the strategy people relied on. A second and a third study showed that framing a cue with high validity as social information facilitated learning to rely on a non-compensatory decision strategy. Overall, the results suggest that social in comparison to non-social information is given more attention and is learned faster than non-social information. Copyright © 2017 Elsevier B.V. All rights reserved.

Hypothesis-confirming information search strategies and computerized information-retrieval systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacobs, S.M.

A recent trend in information-retrieval systems technology is the development of on-line information retrieval systems. One objective of these systems has been to attempt to enhance decision effectiveness by allowing users to preferentially seek information, thereby facilitating the reduction or elimination of information overload. These systems do not necessarily lead to more-effective decision making, however. Recent research in information-search strategy suggests that when users are seeking information subsequent to forming initial beliefs, they may preferentially seek information to confirm these beliefs. It seems that effective computer-based decision support requires an information retrieval system capable of: (a) retrieving a subset ofmore » all available information, in order to reduce information overload, and (b) supporting an information search strategy that considers all relevant information, rather than merely hypothesis-confirming information. An information retrieval system with an expert component (i.e., a knowledge-based DSS) should be able to provide these capabilities. Results of this study are non conclusive; there was neither strong confirmatory evidence nor strong disconfirmatory evidence regarding the effectiveness of the KBDSS.« less

Analysis of Online Information Searching for Cardiovascular Diseases on a Consumer Health Information Portal

PubMed Central

Jadhav, Ashutosh; Sheth, Amit; Pathak, Jyotishman

2014-01-01

Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We analyzed structural properties, types (keyword-based/Wh-questions/Yes-No questions) and linguistic structure of the queries. Our results show that the most searched health categories are ‘Diseases/Conditions’, ‘Vital-Sings’, ‘Symptoms’ and ‘Living-with’. CVD queries are longer and are predominantly keyword-based. This study extends our knowledge about online health information searching and provides useful insights for Web search engines and health websites. PMID:25954380

The Dynamics of Information Search Services.

ERIC Educational Resources Information Center

Lindquist, Mats G.

Computer-based information search services (ISSs) of the type that provide online literature searches are analyzed from a systems viewpoint using a continuous simulation model. The methodology applied is "system dynamics," and the system language is DYNAMO. The analysis reveals that the observed growth and stagnation of a typical ISS can…

'Meatball searching' - The adversarial approach to online information retrieval

NASA Technical Reports Server (NTRS)

Jack, R. F.

1985-01-01

It is proposed that the different styles of online searching can be described as either formal (highly precise) or informal with the needs of the client dictating which is most applicable at a particular moment. The background and personality of the searcher also come into play. Particular attention is focused on meatball searching which is a form of online searching characterized by deliberate vagueness. It requires generally comprehensive searches, often on unusual topics and with tight deadlines. It is most likely to occur in search centers serving many different disciplines and levels of client information sophistication. Various information needs are outlined as well as the laws of meatball searching and the adversarial approach. Traits and characteristics important to sucessful searching include: (1) concept analysis, (2) flexibility of thinking, (3) ability to think in synonyms and (4) anticipation of variant word forms and spellings.

Online health information seeking: the influence of age, information trustworthiness, and search challenges.

PubMed

Miller, Lisa M Soederberg; Bell, Robert A

2012-04-01

The Internet holds great potential to support information gathering and decision making surrounding health education and self-care. Older adults, however, underutilize the Internet for health information searches relative to younger adults. The goal of the present study was to examine age differences in the role of trust and ease of search in predicting whether or not individuals use (adopters) or do notuse (nonadopters) the Internet to search for health information. We used logistic regressions todetermine whether there were age differences in the extent to which trust and ease of search predicted online health information searches within a nationally-representative sample of 3796 adults from the Health Information National Trends Survey (HINTS). Adopters were more trusting of Internet health informationthan nonadopters. However, a significant age by trust interaction indicated that this difference increased in magnitude with age, a pattern that held even after controlling for demographic and health variables. Older adults may benefit from special instructions designed to boost Internet trust, for example, learning how to distinguish between high and low quality health-related websites.

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

PubMed Central

Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379

Information sources in biomedical science and medical journalism: methodological approaches and assessment.

PubMed

Miranda, Giovanna F; Vercellesi, Luisa; Bruno, Flavia

2004-09-01

Throughout the world the public is showing increasing interest in medical and scientific subjects and journalists largely spread this information, with an important impact on knowledge and health. Clearly, therefore, the relationship between the journalist and his sources is delicate: freedom and independence of information depend on the independence and truthfulness of the sources. The new "precision journalism" holds that scientific methods should be applied to journalism, so authoritative sources are a common need for journalists and scientists. We therefore compared the individual classifications and methods of assessing of sources in biomedical science and medical journalism to try to extrapolate scientific methods of evaluation to journalism. In journalism and science terms used to classify sources of information show some similarities, but their meanings are different. In science primary and secondary classes of information, for instance, refer to the levels of processing, but in journalism to the official nature of the source itself. Scientists and journalists must both always consult as many sources as possible and check their authoritativeness, reliability, completeness, up-to-dateness and balance. In journalism, however, there are some important differences and limits: too many sources can sometimes diminish the quality of the information. The sources serve a first filter between the event and the journalist, who is not providing the reader with the fact, but with its projection. Journalists have time constraints and lack the objective criteria for searching, the specific background knowledge, and the expertise to fully assess sources. To assist in understanding the wealth of sources of information in journalism, we have prepared a checklist of items and questions. There are at least four fundamental points that a good journalist, like any scientist, should know: how to find the latest information (the sources), how to assess it (the quality and

PubMed searches: overview and strategies for clinicians.

PubMed

Lindsey, Wesley T; Olin, Bernie R

2013-04-01

PubMed is a biomedical and life sciences database maintained by a division of the National Library of Medicine known as the National Center for Biotechnology Information (NCBI). It is a large resource with more than 5600 journals indexed and greater than 22 million total citations. Searches conducted in PubMed provide references that are more specific for the intended topic compared with other popular search engines. Effective PubMed searches allow the clinician to remain current on the latest clinical trials, systematic reviews, and practice guidelines. PubMed continues to evolve by allowing users to create a customized experience through the My NCBI portal, new arrangements and options in search filters, and supporting scholarly projects through exportation of citations to reference managing software. Prepackaged search options available in the Clinical Queries feature also allow users to efficiently search for clinical literature. PubMed also provides information regarding the source journals themselves through the Journals in NCBI Databases link. This article provides an overview of the PubMed database's structure and features as well as strategies for conducting an effective search.

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

PubMed

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

Biomedical and Health Informatics Education – the IMIA Years

PubMed Central

2016-01-01

Summary Objective This paper presents the development of medical informatics education during the years from the establishment of the International Medical Informatics Association (IMIA) until today. Method A search in the literature was performed using search engines and appropriate keywords as well as a manual selection of papers. The search covered English language papers and was limited to search on papers title and abstract only. Results The aggregated papers were analyzed on the basis of the subject area, origin, time span, and curriculum development, and conclusions were drawn. Conclusions From the results, it is evident that IMIA has played a major role in comparing and integrating the Biomedical and Health Informatics educational efforts across the different levels of education and the regional distribution of educators and institutions. A large selection of references is presented facilitating future work on the field of education in biomedical and health informatics. PMID:27488405

Institute for Scientific Information-indexed biomedical journals of Saudi Arabia. Their performance from 2007-2014.

PubMed

Rohra, Dileep K; Rohra, Vikram K; Cahusac, Peter

2016-11-01

To compare the journal impact factor (JIF) and Eigenfactor score (ES) of Institute for Scientific Information (ISI)-indexed biomedical journals published from the Kingdom of Saudi Arabia (KSA) over the last 8 years. Methods: This is a retrospective study, conducted at Alfaisal University, Riyadh, KSA from January to March 2016. The Journal Citation Reports of ISI Web of Knowledge were accessed, and 6 Saudi biomedical journals were included for analysis. Results: All Saudi journals have improved their IF compared with their baseline. However, the performance of the Journal of Pharmaceutical Sciences and Neurosciences has been exceptionally good. The biggest improvement in percent growth in JIF was seen in the Saudi Pharmaceutical Journal (approximately 887%) followed by Neurosciences (approximately 462%). Interestingly, the ES of all biomedical journals, except Saudi Journal of Gastroenterology and Saudi Medical Journal, increased over the years. The greatest growth in ES (more than 5 fold) was noted for Neurosciences and Saudi Pharmaceutical Journal. Conclusion: This study shows that the overall quality of all Saudi biomedical journals has improved in the last 8 years.

Growth Dynamics of Information Search Services.

ERIC Educational Resources Information Center

Lindqvist, Mats

Computer based information search services, ISS's, of the type that provide on-line literature searches are analyzed from a system's viewpoint using a continuous simulation model. The analysis shows that the observed growth and stagnation of a typical ISS can be explained as a natural consequence of market responses to the service together with a…

Window classification of brain CT images in biomedical articles.

PubMed

Xue, Zhiyun; Antani, Sameer; Long, L Rodney; Demner-Fushman, Dina; Thoma, George R

2012-01-01

Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine.

PubMed

Ping, Peipei; Hermjakob, Henning; Polson, Jennifer S; Benos, Panagiotis V; Wang, Wei

2018-04-27

In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease. © 2018 American Heart Association, Inc.

Informed consent document improvement does not increase patients' comprehension in biomedical research

PubMed Central

Paris, Adeline; Brandt, Christian; Cornu, Catherine; Maison, Patrick; Thalamas, Claire; Cracowski, Jean-Luc

2010-01-01

AIMS International guidelines on ethics in biomedical research require that the informed consent of all enrolled participants is obtained. A written document describing the research, the informed consent (IC) document, must be given to all participants by the investigator. Most IC documents are long, containing much information. The aim of the present study was to determine whether the modification of the IC document by a working group or systematic improvement in its lexicosyntactic readability can improve comprehension of the written information given to patients participating in biomedical research. METHODS One hundred and fifty-nine patients were randomized to read one of the three versions of the IC document: unchanged document, document modified using systematic improvement of lexicosyntactic readability and document modified by a working group. RESULTS Neither the improvement in the lexicosyntactic readability, nor the intervention of the working group significantly improved the score of objective comprehension for the subjects included in this study: it was 66.6 (95% confidence interval 64.0, 69.2) for the control group, 68.8 (66.2, 71.4) for the group with the document improved for lexicosyntactic readability and 69.2 (66.0, 72.4) for the group who read the document improved by the working group (P= 0.38). CONCLUSIONS We failed to show that improving IC document comprehension through a lexicosyntactic approach or by a working group leads to better comprehension. PMID:20233193

An Improved Forensic Science Information Search.

PubMed

Teitelbaum, J

2015-01-01

Although thousands of search engines and databases are available online, finding answers to specific forensic science questions can be a challenge even to experienced Internet users. Because there is no central repository for forensic science information, and because of the sheer number of disciplines under the forensic science umbrella, forensic scientists are often unable to locate material that is relevant to their needs. The author contends that using six publicly accessible search engines and databases can produce high-quality search results. The six resources are Google, PubMed, Google Scholar, Google Books, WorldCat, and the National Criminal Justice Reference Service. Carefully selected keywords and keyword combinations, designating a keyword phrase so that the search engine will search on the phrase and not individual keywords, and prompting search engines to retrieve PDF files are among the techniques discussed. Copyright © 2015 Central Police University.

The Use of Web Search Engines in Information Science Research.

ERIC Educational Resources Information Center

Bar-Ilan, Judit

2004-01-01

Reviews the literature on the use of Web search engines in information science research, including: ways users interact with Web search engines; social aspects of searching; structure and dynamic nature of the Web; link analysis; other bibliometric applications; characterizing information on the Web; search engine evaluation and improvement; and…

Development of health information search engine based on metadata and ontology.

PubMed

Song, Tae-Min; Park, Hyeoun-Ae; Jin, Dal-Lae

2014-04-01

The aim of the study was to develop a metadata and ontology-based health information search engine ensuring semantic interoperability to collect and provide health information using different application programs. Health information metadata ontology was developed using a distributed semantic Web content publishing model based on vocabularies used to index the contents generated by the information producers as well as those used to search the contents by the users. Vocabulary for health information ontology was mapped to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and a list of about 1,500 terms was proposed. The metadata schema used in this study was developed by adding an element describing the target audience to the Dublin Core Metadata Element Set. A metadata schema and an ontology ensuring interoperability of health information available on the internet were developed. The metadata and ontology-based health information search engine developed in this study produced a better search result compared to existing search engines. Health information search engine based on metadata and ontology will provide reliable health information to both information producer and information consumers.

Technical editing of research reports in biomedical journals.

PubMed

Wager, Elizabeth; Middleton, Philippa

2008-10-08

Most journals try to improve their articles by technical editing processes such as proof-reading, editing to conform to 'house styles', grammatical conventions and checking accuracy of cited references. Despite the considerable resources devoted to technical editing, we do not know whether it improves the accessibility of biomedical research findings or the utility of articles. This is an update of a Cochrane methodology review first published in 2003. To assess the effects of technical editing on research reports in peer-reviewed biomedical journals, and to assess the level of accuracy of references to these reports. We searched The Cochrane Library Issue 2, 2007; MEDLINE (last searched July 2006); EMBASE (last searched June 2007) and checked relevant articles for further references. We also searched the Internet and contacted researchers and experts in the field. Prospective or retrospective comparative studies of technical editing processes applied to original research articles in biomedical journals, as well as studies of reference accuracy. Two review authors independently assessed each study against the selection criteria and assessed the methodological quality of each study. One review author extracted the data, and the second review author repeated this. We located 32 studies addressing technical editing and 66 surveys of reference accuracy. Only three of the studies were randomised controlled trials. A 'package' of largely unspecified editorial processes applied between acceptance and publication was associated with improved readability in two studies and improved reporting quality in another two studies, while another study showed mixed results after stricter editorial policies were introduced. More intensive editorial processes were associated with fewer errors in abstracts and references. Providing instructions to authors was associated with improved reporting of ethics requirements in one study and fewer errors in references in two studies, but no

Comparing Web search engine performance in searching consumer health information: evaluation and recommendations.

PubMed Central

Wu, G; Li, J

1999-01-01

Identifying and accessing reliable, relevant consumer health information rapidly on the Internet may challenge the health sciences librarian and layperson alike. In this study, seven search engines are compared using representative consumer health topics for their content relevancy, system features, and attributes. The paper discusses evaluation criteria; systematically compares relevant results; analyzes performance in terms of the strengths and weaknesses of the search engines; and illustrates effective search engine selection, search formulation, and strategies. PMID:10550031

Who Searches the Internet for Health Information?

PubMed Central

Bundorf, M Kate; Wagner, Todd H; Singer, Sara J; Baker, Laurence C

2006-01-01

Objective To determine what types of consumers use the Internet as a source of health information Data Sources A survey of consumer use of the Internet for health information conducted during December 2001 and January 2002 Study Design We estimated multivariate regression models to test hypotheses regarding the characteristics of consumers that affect information seeking behavior Data Collection Respondents were randomly sampled from an Internet-enabled panel of over 60,000 households. Our survey was sent to 12,878 panel members, and 69.4 percent of surveyed panel members responded. We collected information about respondents' use of the Internet to search for health information and to communicate about health care with others using the Internet or e-mail within the last year Principal Findings Individuals with reported chronic conditions were more likely than those without to search for health information on the Internet. The uninsured, particularly those with a reported chronic condition, were more likely than the privately insured to search. Individuals with longer travel times for their usual source of care were more likely to use the Internet for health-related communication than those with shorter travel times Conclusions Populations with serious health needs and those facing significant barriers in accessing health care in traditional settings turn to the Internet for health information. PMID:16704514

Using Internet Search Engines to Obtain Medical Information: A Comparative Study

PubMed Central

Wang, Liupu; Wang, Juexin; Wang, Michael; Li, Yong; Liang, Yanchun

2012-01-01

Background The Internet has become one of the most important means to obtain health and medical information. It is often the first step in checking for basic information about a disease and its treatment. The search results are often useful to general users. Various search engines such as Google, Yahoo!, Bing, and Ask.com can play an important role in obtaining medical information for both medical professionals and lay people. However, the usability and effectiveness of various search engines for medical information have not been comprehensively compared and evaluated. Objective To compare major Internet search engines in their usability of obtaining medical and health information. Methods We applied usability testing as a software engineering technique and a standard industry practice to compare the four major search engines (Google, Yahoo!, Bing, and Ask.com) in obtaining health and medical information. For this purpose, we searched the keyword breast cancer in Google, Yahoo!, Bing, and Ask.com and saved the results of the top 200 links from each search engine. We combined nonredundant links from the four search engines and gave them to volunteer users in an alphabetical order. The volunteer users evaluated the websites and scored each website from 0 to 10 (lowest to highest) based on the usefulness of the content relevant to breast cancer. A medical expert identified six well-known websites related to breast cancer in advance as standards. We also used five keywords associated with breast cancer defined in the latest release of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) and analyzed their occurrence in the websites. Results Each search engine provided rich information related to breast cancer in the search results. All six standard websites were among the top 30 in search results of all four search engines. Google had the best search validity (in terms of whether a website could be opened), followed by Bing, Ask.com, and Yahoo!. The search

Using Internet search engines to obtain medical information: a comparative study.

PubMed

Wang, Liupu; Wang, Juexin; Wang, Michael; Li, Yong; Liang, Yanchun; Xu, Dong

2012-05-16

The Internet has become one of the most important means to obtain health and medical information. It is often the first step in checking for basic information about a disease and its treatment. The search results are often useful to general users. Various search engines such as Google, Yahoo!, Bing, and Ask.com can play an important role in obtaining medical information for both medical professionals and lay people. However, the usability and effectiveness of various search engines for medical information have not been comprehensively compared and evaluated. To compare major Internet search engines in their usability of obtaining medical and health information. We applied usability testing as a software engineering technique and a standard industry practice to compare the four major search engines (Google, Yahoo!, Bing, and Ask.com) in obtaining health and medical information. For this purpose, we searched the keyword breast cancer in Google, Yahoo!, Bing, and Ask.com and saved the results of the top 200 links from each search engine. We combined nonredundant links from the four search engines and gave them to volunteer users in an alphabetical order. The volunteer users evaluated the websites and scored each website from 0 to 10 (lowest to highest) based on the usefulness of the content relevant to breast cancer. A medical expert identified six well-known websites related to breast cancer in advance as standards. We also used five keywords associated with breast cancer defined in the latest release of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) and analyzed their occurrence in the websites. Each search engine provided rich information related to breast cancer in the search results. All six standard websites were among the top 30 in search results of all four search engines. Google had the best search validity (in terms of whether a website could be opened), followed by Bing, Ask.com, and Yahoo!. The search results highly overlapped between the

Finding relevant biomedical datasets: the UC San Diego solution for the bioCADDIE Retrieval Challenge

PubMed Central

Wei, Wei; Ji, Zhanglong; He, Yupeng; Zhang, Kai; Ha, Yuanchi; Li, Qi; Ohno-Machado, Lucila

2018-01-01

Abstract The number and diversity of biomedical datasets grew rapidly in the last decade. A large number of datasets are stored in various repositories, with different formats. Existing dataset retrieval systems lack the capability of cross-repository search. As a result, users spend time searching datasets in known repositories, and they typically do not find new repositories. The biomedical and healthcare data discovery index ecosystem (bioCADDIE) team organized a challenge to solicit new indexing and searching strategies for retrieving biomedical datasets across repositories. We describe the work of one team that built a retrieval pipeline and examined its performance. The pipeline used online resources to supplement dataset metadata, automatically generated queries from users’ free-text questions, produced high-quality retrieval results and achieved the highest inferred Normalized Discounted Cumulative Gain among competitors. The results showed that it is a promising solution for cross-database, cross-domain and cross-repository biomedical dataset retrieval. Database URL: https://github.com/w2wei/dataset_retrieval_pipeline PMID:29688374

Development of Health Information Search Engine Based on Metadata and Ontology

PubMed Central

Song, Tae-Min; Jin, Dal-Lae

2014-01-01

Objectives The aim of the study was to develop a metadata and ontology-based health information search engine ensuring semantic interoperability to collect and provide health information using different application programs. Methods Health information metadata ontology was developed using a distributed semantic Web content publishing model based on vocabularies used to index the contents generated by the information producers as well as those used to search the contents by the users. Vocabulary for health information ontology was mapped to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and a list of about 1,500 terms was proposed. The metadata schema used in this study was developed by adding an element describing the target audience to the Dublin Core Metadata Element Set. Results A metadata schema and an ontology ensuring interoperability of health information available on the internet were developed. The metadata and ontology-based health information search engine developed in this study produced a better search result compared to existing search engines. Conclusions Health information search engine based on metadata and ontology will provide reliable health information to both information producer and information consumers. PMID:24872907

Searching for cancer information on the internet: analyzing natural language search queries.

PubMed

Bader, Judith L; Theofanos, Mary Frances

2003-12-11

Searching for health information is one of the most-common tasks performed by Internet users. Many users begin searching on popular search engines rather than on prominent health information sites. We know that many visitors to our (National Cancer Institute) Web site, cancer.gov, arrive via links in search engine result. To learn more about the specific needs of our general-public users, we wanted to understand what lay users really wanted to know about cancer, how they phrased their questions, and how much detail they used. The National Cancer Institute partnered with AskJeeves, Inc to develop a methodology to capture, sample, and analyze 3 months of cancer-related queries on the Ask.com Web site, a prominent United States consumer search engine, which receives over 35 million queries per week. Using a benchmark set of 500 terms and word roots supplied by the National Cancer Institute, AskJeeves identified a test sample of cancer queries for 1 week in August 2001. From these 500 terms only 37 appeared >or= 5 times/day over the trial test week in 17208 queries. Using these 37 terms, 204165 instances of cancer queries were found in the Ask.com query logs for the actual test period of June-August 2001. Of these, 7500 individual user questions were randomly selected for detailed analysis and assigned to appropriate categories. The exact language of sample queries is presented. Considering multiples of the same questions, the sample of 7500 individual user queries represented 76077 queries (37% of the total 3-month pool). Overall 78.37% of sampled Cancer queries asked about 14 specific cancer types. Within each cancer type, queries were sorted into appropriate subcategories including at least the following: General Information, Symptoms, Diagnosis and Testing, Treatment, Statistics, Definition, and Cause/Risk/Link. The most-common specific cancer types mentioned in queries were Digestive/Gastrointestinal/Bowel (15.0%), Breast (11.7%), Skin (11.3%), and Genitourinary

Searching for Cancer Information on the Internet: Analyzing Natural Language Search Queries

PubMed Central

Theofanos, Mary Frances

2003-01-01

Background Searching for health information is one of the most-common tasks performed by Internet users. Many users begin searching on popular search engines rather than on prominent health information sites. We know that many visitors to our (National Cancer Institute) Web site, cancer.gov, arrive via links in search engine result. Objective To learn more about the specific needs of our general-public users, we wanted to understand what lay users really wanted to know about cancer, how they phrased their questions, and how much detail they used. Methods The National Cancer Institute partnered with AskJeeves, Inc to develop a methodology to capture, sample, and analyze 3 months of cancer-related queries on the Ask.com Web site, a prominent United States consumer search engine, which receives over 35 million queries per week. Using a benchmark set of 500 terms and word roots supplied by the National Cancer Institute, AskJeeves identified a test sample of cancer queries for 1 week in August 2001. From these 500 terms only 37 appeared ≥ 5 times/day over the trial test week in 17208 queries. Using these 37 terms, 204165 instances of cancer queries were found in the Ask.com query logs for the actual test period of June-August 2001. Of these, 7500 individual user questions were randomly selected for detailed analysis and assigned to appropriate categories. The exact language of sample queries is presented. Results Considering multiples of the same questions, the sample of 7500 individual user queries represented 76077 queries (37% of the total 3-month pool). Overall 78.37% of sampled Cancer queries asked about 14 specific cancer types. Within each cancer type, queries were sorted into appropriate subcategories including at least the following: General Information, Symptoms, Diagnosis and Testing, Treatment, Statistics, Definition, and Cause/Risk/Link. The most-common specific cancer types mentioned in queries were Digestive/Gastrointestinal/Bowel (15.0%), Breast (11

Quality of anaesthesia-related information accessed via Internet searches.

PubMed

Caron, S; Berton, J; Beydon, L

2007-08-01

We conducted a study to examine the quality and stability of information available from the Internet on four anaesthesia-related topics. In January 2006, we searched using four key words (porphyria, scleroderma, transfusion risk, and epidural analgesia risk) with five search engines (Google, HotBot, AltaVista, Excite, and Yahoo). We used a published scoring system (NetScoring) to evaluate the first 15 sites identified by each of these 20 searches. We also used a simple four-point scale to assess the first 100 sites in the Google search on one of our four topics ('epidural analgesia risk'). In November 2006, we conducted a second evaluation, using three search engines (Google, AltaVista, and Yahoo) with 14 synonyms for 'epidural analgesia risk'. The five search engines performed similarly. NetScoring scores were lower for transfusion risk (P < 0.001). One or more high-quality sites was identified consistently among the first 15 sites in each search. Quality scored using the simple scale correlated closely with medical content and design by NetScoring and with the number of references (P < 0.05). Synonyms of 'epidural analgesia risk' yielded similar results. The quality of accessed information improved somewhat over the 11 month period with Yahoo and AltaVista, but declined with Google. The Internet is a valuable tool for obtaining medical information, but the quality of websites varies between different topics. A simple rating scale may facilitate the quality scoring on individual websites. Differences in precise search terms used for a given topic did not appear to affect the quality of the information obtained.

Role of Kinetic Modeling in Biomedical Imaging

PubMed Central

Huang, Sung-Cheng

2009-01-01

Biomedical imaging can reveal clear 3-dimensional body morphology non-invasively with high spatial resolution. Its efficacy, in both clinical and pre-clinical settings, is enhanced with its capability to provide in vivo functional/biological information in tissue. The role of kinetic modeling in providing biological/functional information in biomedical imaging is described. General characteristics and limitations in extracting biological information are addressed and practical approaches to solve the problems are discussed and illustrated with examples. Some future challenges and opportunities for kinetic modeling to expand the capability of biomedical imaging are also presented. PMID:20640185

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

PubMed Central

Spjuth, Ola; Krestyaninova, Maria; Hastings, Janna; Shen, Huei-Yi; Heikkinen, Jani; Waldenberger, Melanie; Langhammer, Arnulf; Ladenvall, Claes; Esko, Tõnu; Persson, Mats-Åke; Heggland, Jon; Dietrich, Joern; Ose, Sandra; Gieger, Christian; Ried, Janina S; Peters, Annette; Fortier, Isabel; de Geus, Eco JC; Klovins, Janis; Zaharenko, Linda; Willemsen, Gonneke; Hottenga, Jouke-Jan; Litton, Jan-Eric; Karvanen, Juha; Boomsma, Dorret I; Groop, Leif; Rung, Johan; Palmgren, Juni; Pedersen, Nancy L; McCarthy, Mark I; van Duijn, Cornelia M; Hveem, Kristian; Metspalu, Andres; Ripatti, Samuli; Prokopenko, Inga; Harris, Jennifer R

2016-01-01

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase. PMID:26306643

How Adolescents Search for and Appraise Online Health Information: A Systematic Review.

PubMed

Freeman, Jaimie L; Caldwell, Patrina H Y; Bennett, Patricia A; Scott, Karen M

2018-04-01

To conduct a systematic review of the evidence concerning whether and how adolescents search for online health information and the extent to which they appraise the credibility of information they retrieve. A systematic search of online databases (MEDLINE, EMBASE, PsycINFO, ERIC) was performed. Reference lists of included papers were searched manually for additional articles. Included were studies on whether and how adolescents searched for and appraised online health information, where adolescent participants were aged 13-18 years. Thematic analysis was used to synthesize the findings. Thirty-four studies met the inclusion criteria. In line with the research questions, 2 key concepts were identified within the papers: whether and how adolescents search for online health information, and the extent to which adolescents appraise online health information. Four themes were identified regarding whether and how adolescents search for online health information: use of search engines, difficulties in selecting appropriate search strings, barriers to searching, and absence of searching. Four themes emerged concerning the extent to which adolescents appraise the credibility of online health information: evaluation based on Web site name and reputation, evaluation based on first impression of Web site, evaluation of Web site content, and absence of a sophisticated appraisal strategy. Adolescents are aware of the varying quality of online health information. Strategies used by individuals for searching and appraising online health information differ in their sophistication. It is important to develop resources to enhance search and appraisal skills and to collaborate with adolescents to ensure that such resources are appropriate for them. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-field query expansion is effective for biomedical dataset retrieval

PubMed Central

2017-01-01

Abstract In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data

A tutorial on information retrieval: basic terms and concepts

PubMed Central

Zhou, Wei; Smalheiser, Neil R; Yu, Clement

2006-01-01

This informal tutorial is intended for investigators and students who would like to understand the workings of information retrieval systems, including the most frequently used search engines: PubMed and Google. Having a basic knowledge of the terms and concepts of information retrieval should improve the efficiency and productivity of searches. As well, this knowledge is needed in order to follow current research efforts in biomedical information retrieval and text mining that are developing new systems not only for finding documents on a given topic, but extracting and integrating knowledge across documents. PMID:16722601

EIIS: An Educational Information Intelligent Search Engine Supported by Semantic Services

ERIC Educational Resources Information Center

Huang, Chang-Qin; Duan, Ru-Lin; Tang, Yong; Zhu, Zhi-Ting; Yan, Yong-Jian; Guo, Yu-Qing

2011-01-01

The semantic web brings a new opportunity for efficient information organization and search. To meet the special requirements of the educational field, this paper proposes an intelligent search engine enabled by educational semantic support service, where three kinds of searches are integrated into Educational Information Intelligent Search (EIIS)…

Confirming Preferences or Collecting Data? Information Search Strategies and Romantic Partner Selection

PubMed Central

Hennessy, Michael; Fishbein, Martin; Curtis, Brenda; Barrett, Daniel W.

2010-01-01

This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed 5 types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be “confirmatory bias.” PMID:18350465

Confirming preferences or collecting data? Information search strategies and romantic partner selection.

PubMed

Hennessy, Michael H; Fishbein, Marty; Curtis, Brenda; Barrett, Daniel

2008-03-01

This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed five types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be "confirmatory bias."

Use of Web Search Engines and Personalisation in Information Searching for Educational Purposes

ERIC Educational Resources Information Center

Salehi, Sara; Du, Jia Tina; Ashman, Helen

2018-01-01

Introduction: Students increasingly depend on Web search for educational purposes. This causes concerns among education providers as some evidence indicates that in higher education, the disadvantages of Web search and personalised information are not justified by the benefits. Method: One hundred and twenty university students were surveyed about…

Reinforcement Learning in Information Searching

ERIC Educational Resources Information Center

Cen, Yonghua; Gan, Liren; Bai, Chen

2013-01-01

Introduction: The study seeks to answer two questions: How do university students learn to use correct strategies to conduct scholarly information searches without instructions? and, What are the differences in learning mechanisms between users at different cognitive levels? Method: Two groups of users, thirteen first year undergraduate students…

Literature searches on Ayurveda: An update

PubMed Central

Aggithaya, Madhur G.; Narahari, Saravu R.

2015-01-01

Introduction: The journals that publish on Ayurveda are increasingly indexed by popular medical databases in recent years. However, many Eastern journals are not indexed biomedical journal databases such as PubMed. Literature searches for Ayurveda continue to be challenging due to the nonavailability of active, unbiased dedicated databases for Ayurvedic literature. In 2010, authors identified 46 databases that can be used for systematic search of Ayurvedic papers and theses. This update reviewed our previous recommendation and identified current and relevant databases. Aims: To update on Ayurveda literature search and strategy to retrieve maximum publications. Methods: Author used psoriasis as an example to search previously listed databases and identify new. The population, intervention, control, and outcome table included keywords related to psoriasis and Ayurvedic terminologies for skin diseases. Current citation update status, search results, and search options of previous databases were assessed. Eight search strategies were developed. Hundred and five journals, both biomedical and Ayurveda, which publish on Ayurveda, were identified. Variability in databases was explored to identify bias in journal citation. Results: Five among 46 databases are now relevant – AYUSH research portal, Annotated Bibliography of Indian Medicine, Digital Helpline for Ayurveda Research Articles (DHARA), PubMed, and Directory of Open Access Journals. Search options in these databases are not uniform, and only PubMed allows complex search strategy. “The Researches in Ayurveda” and “Ayurvedic Research Database” (ARD) are important grey resources for hand searching. About 44/105 (41.5%) journals publishing Ayurvedic studies are not indexed in any database. Only 11/105 (10.4%) exclusive Ayurveda journals are indexed in PubMed. Conclusion: AYUSH research portal and DHARA are two major portals after 2010. It is mandatory to search PubMed and four other databases because all five

Literature searches on Ayurveda: An update.

PubMed

Aggithaya, Madhur G; Narahari, Saravu R

2015-01-01

The journals that publish on Ayurveda are increasingly indexed by popular medical databases in recent years. However, many Eastern journals are not indexed biomedical journal databases such as PubMed. Literature searches for Ayurveda continue to be challenging due to the nonavailability of active, unbiased dedicated databases for Ayurvedic literature. In 2010, authors identified 46 databases that can be used for systematic search of Ayurvedic papers and theses. This update reviewed our previous recommendation and identified current and relevant databases. To update on Ayurveda literature search and strategy to retrieve maximum publications. Author used psoriasis as an example to search previously listed databases and identify new. The population, intervention, control, and outcome table included keywords related to psoriasis and Ayurvedic terminologies for skin diseases. Current citation update status, search results, and search options of previous databases were assessed. Eight search strategies were developed. Hundred and five journals, both biomedical and Ayurveda, which publish on Ayurveda, were identified. Variability in databases was explored to identify bias in journal citation. Five among 46 databases are now relevant - AYUSH research portal, Annotated Bibliography of Indian Medicine, Digital Helpline for Ayurveda Research Articles (DHARA), PubMed, and Directory of Open Access Journals. Search options in these databases are not uniform, and only PubMed allows complex search strategy. "The Researches in Ayurveda" and "Ayurvedic Research Database" (ARD) are important grey resources for hand searching. About 44/105 (41.5%) journals publishing Ayurvedic studies are not indexed in any database. Only 11/105 (10.4%) exclusive Ayurveda journals are indexed in PubMed. AYUSH research portal and DHARA are two major portals after 2010. It is mandatory to search PubMed and four other databases because all five carry citations from different groups of journals. The hand

Adolescents Searching for Health Information on the Internet: An Observational Study

PubMed Central

Derry, Holly A; Resnick, Paul J; Richardson, Caroline R

2003-01-01

Background Adolescents' access to health information on the Internet is partly a function of their ability to search for and find answers to their health-related questions. Adolescents may have unique health and computer literacy needs. Although many surveys, interviews, and focus groups have been utilized to understand the information-seeking and information-retrieval behavior of adolescents looking for health information online, we were unable to locate observations of individual adolescents that have been conducted in this context. Objective This study was designed to understand how adolescents search for health information using the Internet and what implications this may have on access to health information. Methods A convenience sample of 12 students (age 12-17 years) from 1 middle school and 2 high schools in southeast Michigan were provided with 6 health-related questions and asked to look for answers using the Internet. Researchers recorded 68 specific searches using software that captured screen images as well as synchronized audio recordings. Recordings were reviewed later and specific search techniques and strategies were coded. A qualitative review of the verbal communication was also performed. Results Out of 68 observed searches, 47 (69%) were successful in that the adolescent found a correct and useful answer to the health question. The majority of sites that students attempted to access were retrieved directly from search engine results (77%) or a search engine's recommended links (10%); only a small percentage were directly accessed (5%) or linked from another site (7%). The majority (83%) of followed links from search engine results came from the first 9 results. Incorrect spelling (30 of 132 search terms), number of pages visited within a site (ranging from 1-15), and overall search strategy (eg, using a search engine versus directly accessing a site), were each important determinants of success. Qualitative analysis revealed that participants

Graduate program in biomedical communication.

PubMed

Ryan, S M

1969-10-01

The need for harnessing the achievements of communication technology to the burgeoning mass of biomedical information is critical. Recognizing this problem and aware of the short supply of professionals with the skills necessary for the job, a group of leaders from the fields of medicine and communications formed a consortium in 1967 and have developed a twelve month graduate program in biomedical communication. Designed to ground the advanced student in the development and administration of biomedical communication programs, the curriculum focuses on the principles and practice of communication and the development of communications media. Courses are given in the control and communication of information; the printed and spoken word; visual media of photographic arts, television, and motion pictures; computer science; and administration and systems analysis.

Graduate Program in Biomedical Communication *

PubMed Central

Ryan, Susan M.

1969-01-01

The need for harnessing the achievements of communication technology to the burgeoning mass of biomedical information is critical. Recognizing this problem and aware of the short supply of professionals with the skills necessary for the job, a group of leaders from the fields of medicine and communications formed a consortium in 1967 and have developed a twelve month graduate program in biomedical communication. Designed to ground the advanced student in the development and administration of biomedical communication programs, the curriculum focuses on the principles and practice of communication and the development of communications media. Courses are given in the control and communication of information; the printed and spoken word; visual media of photographic arts, television, and motion pictures; computer science; and administration and systems analysis. PMID:5823505

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.

PubMed

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung; Lee, Jae Ho

2013-06-01

The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.

A Study on Pubmed Search Tag Usage Pattern: Association Rule Mining of a Full-day Pubmed Query Log

PubMed Central

2013-01-01

Background The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. Methods A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. Results The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. Conclusions The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed’s Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE. PMID:23302604

Frontiers in biomedical engineering and biotechnology.

PubMed

Liu, Feng; Goodarzi, Ali; Wang, Haifeng; Stasiak, Joanna; Sun, Jianbo; Zhou, Yu

2014-01-01

The 2nd International Conference on Biomedical Engineering and Biotechnology (iCBEB 2013), held in Wuhan on 11–13 October 2013, is an annual conference that aims at providing an opportunity for international and national researchers and practitioners to present the most recent advances and future challenges in the fields of Biomedical Information, Biomedical Engineering and Biotechnology. The papers published by this issue are selected from this conference, which witnesses the frontier in the field of Biomedical Engineering and Biotechnology, which particularly has helped improving the level of clinical diagnosis in medical work.

Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

PubMed

Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

2009-01-01

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

BioLemmatizer: a lemmatization tool for morphological processing of biomedical text

PubMed Central

2012-01-01

Background The wide variety of morphological variants of domain-specific technical terms contributes to the complexity of performing natural language processing of the scientific literature related to molecular biology. For morphological analysis of these texts, lemmatization has been actively applied in the recent biomedical research. Results In this work, we developed a domain-specific lemmatization tool, BioLemmatizer, for the morphological analysis of biomedical literature. The tool focuses on the inflectional morphology of English and is based on the general English lemmatization tool MorphAdorner. The BioLemmatizer is further tailored to the biological domain through incorporation of several published lexical resources. It retrieves lemmas based on the use of a word lexicon, and defines a set of rules that transform a word to a lemma if it is not encountered in the lexicon. An innovative aspect of the BioLemmatizer is the use of a hierarchical strategy for searching the lexicon, which enables the discovery of the correct lemma even if the input Part-of-Speech information is inaccurate. The BioLemmatizer achieves an accuracy of 97.5% in lemmatizing an evaluation set prepared from the CRAFT corpus, a collection of full-text biomedical articles, and an accuracy of 97.6% on the LLL05 corpus. The contribution of the BioLemmatizer to accuracy improvement of a practical information extraction task is further demonstrated when it is used as a component in a biomedical text mining system. Conclusions The BioLemmatizer outperforms other tools when compared with eight existing lemmatizers. The BioLemmatizer is released as an open source software and can be downloaded from http://biolemmatizer.sourceforge.net. PMID:22464129

Query Log Analysis of an Electronic Health Record Search Engine

PubMed Central

Yang, Lei; Mei, Qiaozhu; Zheng, Kai; Hanauer, David A.

2011-01-01

We analyzed a longitudinal collection of query logs of a full-text search engine designed to facilitate information retrieval in electronic health records (EHR). The collection, 202,905 queries and 35,928 user sessions recorded over a course of 4 years, represents the information-seeking behavior of 533 medical professionals, including frontline practitioners, coding personnel, patient safety officers, and biomedical researchers for patient data stored in EHR systems. In this paper, we present descriptive statistics of the queries, a categorization of information needs manifested through the queries, as well as temporal patterns of the users’ information-seeking behavior. The results suggest that information needs in medical domain are substantially more sophisticated than those that general-purpose web search engines need to accommodate. Therefore, we envision there exists a significant challenge, along with significant opportunities, to provide intelligent query recommendations to facilitate information retrieval in EHR. PMID:22195150

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically

Searching to Translate and Translating to Search: When Information Retrieval Meets Machine Translation

ERIC Educational Resources Information Center

Ture, Ferhan

2013-01-01

With the adoption of web services in daily life, people have access to tremendous amounts of information, beyond any human's reading and comprehension capabilities. As a result, search technologies have become a fundamental tool for accessing information. Furthermore, the web contains information in multiple languages, introducing another barrier…

Asking better questions: How presentation formats influence information search.

PubMed

Wu, Charley M; Meder, Björn; Filimon, Flavia; Nelson, Jonathan D

2017-08-01

While the influence of presentation formats have been widely studied in Bayesian reasoning tasks, we present the first systematic investigation of how presentation formats influence information search decisions. Four experiments were conducted across different probabilistic environments, where subjects (N = 2,858) chose between 2 possible search queries, each with binary probabilistic outcomes, with the goal of maximizing classification accuracy. We studied 14 different numerical and visual formats for presenting information about the search environment, constructed across 6 design features that have been prominently related to improvements in Bayesian reasoning accuracy (natural frequencies, posteriors, complement, spatial extent, countability, and part-to-whole information). The posterior variants of the icon array and bar graph formats led to the highest proportion of correct responses, and were substantially better than the standard probability format. Results suggest that presenting information in terms of posterior probabilities and visualizing natural frequencies using spatial extent (a perceptual feature) were especially helpful in guiding search decisions, although environments with a mixture of probabilistic and certain outcomes were challenging across all formats. Subjects who made more accurate probability judgments did not perform better on the search task, suggesting that simple decision heuristics may be used to make search decisions without explicitly applying Bayesian inference to compute probabilities. We propose a new take-the-difference (TTD) heuristic that identifies the accuracy-maximizing query without explicit computation of posterior probabilities. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Biomedical informatics and translational medicine.

PubMed

Sarkar, Indra Neil

2010-02-26

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams.

Searching the Internet for information on prostate cancer screening: an assessment of quality.

PubMed

Ilic, Dragan; Risbridger, Gail; Green, Sally

2004-07-01

To identify how on-line information relating to prostate cancer screening (PCS) is best sourced, whether through general, medical, or meta-search engines, and to assess the quality of that information. Websites providing information about PCS were searched across 15 search engines representing three distinct types: general, medical, and meta-search engines. The quality of on-line information was assessed using the DISCERN quality assessment tool. Quality performance characteristics were analyzed by performing Mann-Whitney U tests. Search engine efficiency was measured by each search query as a percentage of the relevant websites included for analysis from the total returned and analyzed by performing Kruskal-Wallis analysis of variance. Of 6690 websites reviewed, 84 unique websites were identified as providing information relevant to PCS. General and meta-search engines were significantly more efficient at retrieving relevant information on PCS compared with medical search engines. The quality of information was variable, with most of a poor standard. Websites that provided referral links to other resources and a citation of evidence provided a significantly better quality of information. In contrast, websites offering a direct service were more likely to provide a significantly poorer quality of information. The current lack of a clear consensus on guidelines and recommendation in published data is also reflected by the variable quality of information found on-line. Specialized medical search engines were no more likely to retrieve relevant, high-quality information than general or meta-search engines.

The SWAN biomedical discourse ontology.

PubMed

Ciccarese, Paolo; Wu, Elizabeth; Wong, Gwen; Ocana, Marco; Kinoshita, June; Ruttenberg, Alan; Clark, Tim

2008-10-01

Developing cures for highly complex diseases, such as neurodegenerative disorders, requires extensive interdisciplinary collaboration and exchange of biomedical information in context. Our ability to exchange such information across sub-specialties today is limited by the current scientific knowledge ecosystem's inability to properly contextualize and integrate data and discourse in machine-interpretable form. This inherently limits the productivity of research and the progress toward cures for devastating diseases such as Alzheimer's and Parkinson's. SWAN (Semantic Web Applications in Neuromedicine) is an interdisciplinary project to develop a practical, common, semantically structured, framework for biomedical discourse initially applied, but not limited, to significant problems in Alzheimer Disease (AD) research. The SWAN ontology has been developed in the context of building a series of applications for biomedical researchers, as well as in extensive discussions and collaborations with the larger bio-ontologies community. In this paper, we present and discuss the SWAN ontology of biomedical discourse. We ground its development theoretically, present its design approach, explain its main classes and their application, and show its relationship to other ongoing activities in biomedicine and bio-ontologies.

Searching for suicide-related information on Chinese websites.

PubMed

Chen, Ying-Yeh; Hung, Galen Chin-Lun; Cheng, Qijin; Tsai, Chi-Wei; Wu, Kevin Chien-Chang

2017-12-01

Growing concerns about cyber-suicide have prompted many studies on suicide information available on the web. However, very few studies have considered non-English websites. We aimed to analyze online suicide-related information accessed through Chinese-language websites. We used Taiwan's two most popular search engines (Google and Yahoo) to explore the results returned from six suicide-related search terms in March 2016. The first three pages listing the results from each search were analyzed and rated based on the attitude towards suicide (pro-suicide, anti-suicide, neutral/mixed, not a suicide site, or error). Comparisons across different search terms were also performed. In all, 375 linked webpages were included; 16.3% of the webpages were pro-suicide and 41.3% were anti-suicide. The majority of the pro-suicide sites were user-generated webpages (96.7%). Searches using the keywords 'ways to kill yourself' (31.7%) and 'painless suicide' (28.3%) generated much larger numbers of harmful webpages than the term 'suicide' (4.3%). We conclude that collaborative efforts with internet service providers and search engines to improve the ranking of anti-suicide webpages and websites and implement online suicide reporting guidelines are highly encouraged. Copyright © 2017 Elsevier B.V. All rights reserved.

Telemedicine optoelectronic biomedical data processing system

NASA Astrophysics Data System (ADS)

Prosolovska, Vita V.

2010-08-01

The telemedicine optoelectronic biomedical data processing system is created to share medical information for the control of health rights and timely and rapid response to crisis. The system includes the main blocks: bioprocessor, analog-digital converter biomedical images, optoelectronic module for image processing, optoelectronic module for parallel recording and storage of biomedical imaging and matrix screen display of biomedical images. Rated temporal characteristics of the blocks defined by a particular triggering optoelectronic couple in analog-digital converters and time imaging for matrix screen. The element base for hardware implementation of the developed matrix screen is integrated optoelectronic couples produced by selective epitaxy.

ISART: A Generic Framework for Searching Books with Social Information

PubMed Central

Cui, Xiao-Ping; Qu, Jiao; Geng, Bin; Zhou, Fang; Song, Li; Hao, Hong-Wei

2016-01-01

Effective book search has been discussed for decades and is still future-proof in areas as diverse as computer science, informatics, e-commerce and even culture and arts. A variety of social information contents (e.g, ratings, tags and reviews) emerge with the huge number of books on the Web, but how they are utilized for searching and finding books is seldom investigated. Here we develop an Integrated Search And Recommendation Technology (IsArt), which breaks new ground by providing a generic framework for searching books with rich social information. IsArt comprises a search engine to rank books with book contents and professional metadata, a Generalized Content-based Filtering model to thereafter rerank books with user-generated social contents, and a learning-to-rank technique to finally combine a wide range of diverse reranking results. Experiments show that this technology permits embedding social information to promote book search effectiveness, and IsArt, by making use of it, has the best performance on CLEF/INEX Social Book Search Evaluation datasets of all 4 years (from 2011 to 2014), compared with some other state-of-the-art methods. PMID:26863545

ISART: A Generic Framework for Searching Books with Social Information.

PubMed

Yin, Xu-Cheng; Zhang, Bo-Wen; Cui, Xiao-Ping; Qu, Jiao; Geng, Bin; Zhou, Fang; Song, Li; Hao, Hong-Wei

2016-01-01

Effective book search has been discussed for decades and is still future-proof in areas as diverse as computer science, informatics, e-commerce and even culture and arts. A variety of social information contents (e.g, ratings, tags and reviews) emerge with the huge number of books on the Web, but how they are utilized for searching and finding books is seldom investigated. Here we develop an Integrated Search And Recommendation Technology (IsArt), which breaks new ground by providing a generic framework for searching books with rich social information. IsArt comprises a search engine to rank books with book contents and professional metadata, a Generalized Content-based Filtering model to thereafter rerank books with user-generated social contents, and a learning-to-rank technique to finally combine a wide range of diverse reranking results. Experiments show that this technology permits embedding social information to promote book search effectiveness, and IsArt, by making use of it, has the best performance on CLEF/INEX Social Book Search Evaluation datasets of all 4 years (from 2011 to 2014), compared with some other state-of-the-art methods.

Searching LOGIN, the Local Government Information Network.

ERIC Educational Resources Information Center

Jack, Robert F.

1984-01-01

Describes a computer-based information retrieval and electronic messaging system produced by Control Data Corporation now being used by government agencies and other organizations. Background of Local Government Information Network (LOGIN), database structure, types of LOGIN units, searching LOGIN (intersect, display, and list commands), and how…

Assessing the impact of case sensitivity and term information gain on biomedical concept recognition.

PubMed

Groza, Tudor; Verspoor, Karin

2015-01-01

Concept recognition (CR) is a foundational task in the biomedical domain. It supports the important process of transforming unstructured resources into structured knowledge. To date, several CR approaches have been proposed, most of which focus on a particular set of biomedical ontologies. Their underlying mechanisms vary from shallow natural language processing and dictionary lookup to specialized machine learning modules. However, no prior approach considers the case sensitivity characteristics and the term distribution of the underlying ontology on the CR process. This article proposes a framework that models the CR process as an information retrieval task in which both case sensitivity and the information gain associated with tokens in lexical representations (e.g., term labels, synonyms) are central components of a strategy for generating term variants. The case sensitivity of a given ontology is assessed based on the distribution of so-called case sensitive tokens in its terms, while information gain is modelled using a combination of divergence from randomness and mutual information. An extensive evaluation has been carried out using the CRAFT corpus. Experimental results show that case sensitivity awareness leads to an increase of up to 0.07 F1 against a non-case sensitive baseline on the Protein Ontology and GO Cellular Component. Similarly, the use of information gain leads to an increase of up to 0.06 F1 against a standard baseline in the case of GO Biological Process and Molecular Function and GO Cellular Component. Overall, subject to the underlying token distribution, these methods lead to valid complementary strategies for augmenting term label sets to improve concept recognition.

Chemical Information in Scirus and BASE (Bielefeld Academic Search Engine)

ERIC Educational Resources Information Center

Bendig, Regina B.

2009-01-01

The author sought to determine to what extent the two search engines, Scirus and BASE (Bielefeld Academic Search Engines), would be useful to first-year university students as the first point of searching for chemical information. Five topics were searched and the first ten records of each search result were evaluated with regard to the type of…

The application of foraging theory to the information searching behaviour of general practitioners.

PubMed

Dwairy, Mai; Dowell, Anthony C; Stahl, Jean-Claude

2011-08-23

General Practitioners (GPs) employ strategies to identify and retrieve medical evidence for clinical decision making which take workload and time constraints into account. Optimal Foraging Theory (OFT) initially developed to study animal foraging for food is used to explore the information searching behaviour of General Practitioners. This study is the first to apply foraging theory within this context.Study objectives were: 1. To identify the sequence and steps deployed in identifiying and retrieving evidence for clinical decision making. 2. To utilise Optimal Foraging Theory to assess the effectiveness and efficiency of General Practitioner information searching. GPs from the Wellington region of New Zealand were asked to document in a pre-formatted logbook the steps and outcomes of an information search linked to their clinical decision making, and fill in a questionnaire about their personal, practice and information-searching backgrounds. A total of 115/155 eligible GPs returned a background questionnaire, and 71 completed their information search logbook. GPs spent an average of 17.7 minutes addressing their search for clinical information. Their preferred information sources were discussions with colleagues (38% of sources) and books (22%). These were the two most profitable information foraging sources (15.9 min and 9.5 min search time per answer, compared to 34.3 minutes in databases). GPs nearly always accessed another source when unsuccessful (95% after 1st source), and frequently when successful (43% after 2nd source). Use of multiple sources accounted for 41% of searches, and increased search success from 70% to 89%. By consulting in foraging terms the most 'profitable' sources of information (colleagues, books), rapidly switching sources when unsuccessful, and frequently double checking, GPs achieve an efficient trade-off between maximizing search success and information reliability, and minimizing searching time. As predicted by foraging theory, GPs

The World Wide Web: a review of an emerging internet-based technology for the distribution of biomedical information.

PubMed Central

Lowe, H J; Lomax, E C; Polonkey, S E

1996-01-01

The Internet is rapidly evolving from a resource used primarily by the research community to a true global information network offering a wide range of databases and services. This evolution presents many opportunities for improved access to biomedical information, but Internet-based resources have often been difficult for the non-expert to develop and use. The World Wide Web (WWW) supports an inexpensive, easy-to-use, cross-platform, graphic interface to the Internet that may radically alter the way we retrieve and disseminate medical data. This paper summarizes the Internet and hypertext origins of the WWW, reviews WWW-specific technologies, and describes current and future applications of this technology in medicine and medical informatics. The paper also includes an appendix of useful biomedical WWW servers. PMID:8750386

A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.

PubMed

Mosa, Abu Saleh Mohammad; Yoo, Illhoi

2013-01-09

The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed's Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE.

Exploration of Global Trend on Biomedical Application of Polyhydroxyalkanoate (PHA): A Patent Survey.

PubMed

Ponnaiah, Paulraj; Vnoothenei, Nagiah; Chandramohan, Muruganandham; Thevarkattil, Mohamed Javad Pazhayakath

2018-01-30

Polyhydroxyalkanoates are bio-based, biodegradable naturally occurring polymers produced by a wide range of organisms, from bacteria to higher mammals. The properties and biocompatibility of PHA make it possible for a wide spectrum of applications. In this context, we analyze the potential applications of PHA in biomedical science by exploring the global trend through the patent survey. The survey suggests that PHA is an attractive candidate in such a way that their applications are widely distributed in the medical industry, drug delivery system, dental material, tissue engineering, packaging material as well as other useful products. In our present study, we explored patents associated with various biomedical applications of polyhydroxyalkanoates. Patent databases of European Patent Office, United States Patent and Trademark Office and World Intellectual Property Organization were mined. We developed an intensive exploration approach to eliminate overlapping patents and sort out significant patents. We demarcated the keywords and search criterions and established search patterns for the database request. We retrieved documents within the recent 6 years, 2010 to 2016 and sort out the collected data stepwise to gather the most appropriate documents in patent families for further scrutiny. By this approach, we retrieved 23,368 patent documents from all the three databases and the patent titles were further analyzed for the relevance of polyhydroxyalkanoates in biomedical applications. This ensued in the documentation of approximately 226 significant patents associated with biomedical applications of polyhydroxyalkanoates and the information was classified into six major groups. Polyhydroxyalkanoates has been patented in such a way that their applications are widely distributed in the medical industry, drug delivery system, dental material, tissue engineering, packaging material as well as other useful products. There are many avenues through which PHA & PHB could be

Extraction of endoscopic images for biomedical figure classification

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; You, Daekeun; Chachra, Suchet; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

Modality filtering is an important feature in biomedical image searching systems and may significantly improve the retrieval performance of the system. This paper presents a new method for extracting endoscopic image figures from photograph images in biomedical literature, which are found to have highly diverse content and large variability in appearance. Our proposed method consists of three main stages: tissue image extraction, endoscopic image candidate extraction, and ophthalmic image filtering. For tissue image extraction we use image patch level clustering and MRF relabeling to detect images containing skin/tissue regions. Next, we find candidate endoscopic images by exploiting the round shape characteristics that commonly appear in these images. However, this step needs to compensate for images where endoscopic regions are not entirely round. In the third step we filter out the ophthalmic images which have shape characteristics very similar to the endoscopic images. We do this by using text information, specifically, anatomy terms, extracted from the figure caption. We tested and evaluated our method on a dataset of 115,370 photograph figures, and achieved promising precision and recall rates of 87% and 84%, respectively.

Learning to rank diversified results for biomedical information retrieval from multiple features.

PubMed

Wu, Jiajin; Huang, Jimmy; Ye, Zheng

2014-01-01

Different from traditional information retrieval (IR), promoting diversity in IR takes consideration of relationship between documents in order to promote novelty and reduce redundancy thus to provide diversified results to satisfy various user intents. Diversity IR in biomedical domain is especially important as biologists sometimes want diversified results pertinent to their query. A combined learning-to-rank (LTR) framework is learned through a general ranking model (gLTR) and a diversity-biased model. The former is learned from general ranking features by a conventional learning-to-rank approach; the latter is constructed with diversity-indicating features added, which are extracted based on the retrieved passages' topics detected using Wikipedia and ranking order produced by the general learning-to-rank model; final ranking results are given by combination of both models. Compared with baselines BM25 and DirKL on 2006 and 2007 collections, the gLTR has 0.2292 (+16.23% and +44.1% improvement over BM25 and DirKL respectively) and 0.1873 (+15.78% and +39.0% improvement over BM25 and DirKL respectively) in terms of aspect level of mean average precision (Aspect MAP). The LTR method outperforms gLTR on 2006 and 2007 collections with 4.7% and 2.4% improvement in terms of Aspect MAP. The learning-to-rank method is an efficient way for biomedical information retrieval and the diversity-biased features are beneficial for promoting diversity in ranking results.

Multi-field query expansion is effective for biomedical dataset retrieval.

PubMed

Bouadjenek, Mohamed Reda; Verspoor, Karin

2017-01-01

In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery

Development and tuning of an original search engine for patent libraries in medicinal chemistry.

PubMed

Pasche, Emilie; Gobeill, Julien; Kreim, Olivier; Oezdemir-Zaech, Fatma; Vachon, Therese; Lovis, Christian; Ruch, Patrick

2014-01-01

The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to adapt to the various search tasks

Augmenting Oracle Text with the UMLS for enhanced searching of free-text medical reports.

PubMed

Ding, Jing; Erdal, Selnur; Dhaval, Rakesh; Kamal, Jyoti

2007-10-11

The intrinsic complexity of free-text medical reports imposes great challenges for information retrieval systems. We have developed a prototype search engine for retrieving clinical reports that leverages the powerful indexing and querying capabilities of Oracle Text, and the rich biomedical domain knowledge and semantic structures that are captured in the UMLS Metathesaurus.

Information Retrieval for Education: Making Search Engines Language Aware

ERIC Educational Resources Information Center

Ott, Niels; Meurers, Detmar

2010-01-01

Search engines have been a major factor in making the web the successful and widely used information source it is today. Generally speaking, they make it possible to retrieve web pages on a topic specified by the keywords entered by the user. Yet web searching currently does not take into account which of the search results are comprehensible for…

Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education.

PubMed

Patel, Vimla L; Yoskowitz, Nicole A; Arocha, Jose F; Shortliffe, Edward H

2009-02-01

Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital

PubMed Central

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung

2013-01-01

Objectives The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. Methods We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. Results The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. Conclusions We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly. PMID:23882415

Academic Users' Information Searching on Research Topics: Characteristics of Research Tasks and Search Strategies

ERIC Educational Resources Information Center

Du, Jia Tina; Evans, Nina

2011-01-01

This project investigated how academic users search for information on their real-life research tasks. This article presents the findings of the first of two studies. The study data were collected in the Queensland University of Technology (QUT) in Brisbane, Australia. Eleven PhD students' searching behaviors on personal research topics were…

Improving validity of informed consent for biomedical research in Zambia using a laboratory exposure intervention.

PubMed

Zulu, Joseph Mumba; Lisulo, Mpala Mwanza; Besa, Ellen; Kaonga, Patrick; Chisenga, Caroline C; Chomba, Mumba; Simuyandi, Michelo; Banda, Rosemary; Kelly, Paul

2014-01-01

Complex biomedical research can lead to disquiet in communities with limited exposure to scientific discussions, leading to rumours or to high drop-out rates. We set out to test an intervention designed to address apprehensions commonly encountered in a community where literacy is uncommon, and where complex biomedical research has been conducted for over a decade. We aimed to determine if it could improve the validity of consent. Data were collected using focus group discussions, key informant interviews and observations. We designed an intervention that exposed participants to a detailed demonstration of laboratory processes. Each group was interviewed twice in a day, before and after exposure to the intervention in order to assess changes in their views. Factors that motivated people to participate in invasive biomedical research included a desire to stay healthy because of the screening during the recruitment process, regular advice from doctors, free medical services, and trust in the researchers. Inhibiting factors were limited knowledge about samples taken from their bodies during endoscopic procedures, the impact of endoscopy on the function of internal organs, and concerns about the use of biomedical samples. The belief that blood can be used for Satanic practices also created insecurities about drawing of blood samples. Further inhibiting factors included a fear of being labelled as HIV positive if known to consult heath workers repeatedly, and gender inequality. Concerns about the use and storage of blood and tissue samples were overcome by a laboratory exposure intervention. Selecting a group of members from target community and engaging them in a laboratory exposure intervention could be a useful tool for enhancing specific aspects of consent for biomedical research. Further work is needed to determine the extent to which improved understanding permeates beyond the immediate group participating in the intervention.

Improving Validity of Informed Consent for Biomedical Research in Zambia Using a Laboratory Exposure Intervention

PubMed Central

Zulu, Joseph Mumba; Lisulo, Mpala Mwanza; Besa, Ellen; Kaonga, Patrick; Chisenga, Caroline C.; Chomba, Mumba; Simuyandi, Michelo; Banda, Rosemary; Kelly, Paul

2014-01-01

Background Complex biomedical research can lead to disquiet in communities with limited exposure to scientific discussions, leading to rumours or to high drop-out rates. We set out to test an intervention designed to address apprehensions commonly encountered in a community where literacy is uncommon, and where complex biomedical research has been conducted for over a decade. We aimed to determine if it could improve the validity of consent. Methods Data were collected using focus group discussions, key informant interviews and observations. We designed an intervention that exposed participants to a detailed demonstration of laboratory processes. Each group was interviewed twice in a day, before and after exposure to the intervention in order to assess changes in their views. Results Factors that motivated people to participate in invasive biomedical research included a desire to stay healthy because of the screening during the recruitment process, regular advice from doctors, free medical services, and trust in the researchers. Inhibiting factors were limited knowledge about samples taken from their bodies during endoscopic procedures, the impact of endoscopy on the function of internal organs, and concerns about the use of biomedical samples. The belief that blood can be used for Satanic practices also created insecurities about drawing of blood samples. Further inhibiting factors included a fear of being labelled as HIV positive if known to consult heath workers repeatedly, and gender inequality. Concerns about the use and storage of blood and tissue samples were overcome by a laboratory exposure intervention. Conclusion Selecting a group of members from target community and engaging them in a laboratory exposure intervention could be a useful tool for enhancing specific aspects of consent for biomedical research. Further work is needed to determine the extent to which improved understanding permeates beyond the immediate group participating in the intervention

Symposium on Career Opportunities in Biomedical and Public Health Sciences

NASA Technical Reports Server (NTRS)

Sullivan, Walter W.

1997-01-01

The goal of the Symposium on Career Opportunities in Biomedical and Public Health Sciences is to encourage minority collegiate and junior and senior high school students to pursue careers in biomedical and public health sciences. The objectives of the Symposium are to: (1) Provide information to participants concerning biomedical and public health science careers in government, academe and industry; (2) Provide information to minority students about training activities necessary to pursue a biomedical or public health science career and the fiscal support that one can obtain for such training; and (3) Provide opportunities for participating minority biomedical and public health role models to interact with participants.

Biomedical image segmentation using geometric deformable models and metaheuristics.

PubMed

Mesejo, Pablo; Valsecchi, Andrea; Marrakchi-Kacem, Linda; Cagnoni, Stefano; Damas, Sergio

2015-07-01

This paper describes a hybrid level set approach for medical image segmentation. This new geometric deformable model combines region- and edge-based information with the prior shape knowledge introduced using deformable registration. Our proposal consists of two phases: training and test. The former implies the learning of the level set parameters by means of a Genetic Algorithm, while the latter is the proper segmentation, where another metaheuristic, in this case Scatter Search, derives the shape prior. In an experimental comparison, this approach has shown a better performance than a number of state-of-the-art methods when segmenting anatomical structures from different biomedical image modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Biomedical and health informatics education and research at the Information Technology Institute in Egypt.

PubMed

Hussein, R; Khalifa, A

2011-01-01

During the last decade, Egypt has experienced a revolution in the field of Information and Communication Technology (ICT) that has had a corresponding impact on the field of healthcare. Since 1993, the Information Technology Institute (ITI) has been leading the development of the Information Technology (IT) professional training and education in Egypt to produce top quality IT professionals who are considered now the backbone of the IT revolution in Egypt. For the past five years, ITI has been adopting the objective of building high caliber health professionals who can effectively serve the ever-growing information society. Academic links have been established with internationally renowned universities, e.g., Oregon Health and Science University (OHSU) in US, University of Leipzig in Germany, in addition those with the Egyptian Fellowship Board in order to enrich ITI Medical Informatics Education and Research. The ITI Biomedical and Health Informatics (BMHI) education and training programs target fresh graduates as well as life-long learners. Therefore, the program's learning objectives are framed within the context of the four specialization tracks: Healthcare Management (HCM), Biomedical Informatics Research (BMIR), Bioinformatics Professional (BIP), and Healthcare Professional (HCP). The ITI BMHI research projects tackle a wide-range of current challenges in this field, such as knowledge management in healthcare, providing tele-consultation services for diagnosis and treatment of infectious diseases for underserved regions in Egypt, and exploring the cultural and educational aspects of Nanoinformatics. Since 2006, ITI has been positively contributing to develop the discipline of BMHI in Egypt in order to support improved healthcare services.

[Scientometrics and bibliometrics of biomedical engineering periodicals and papers].

PubMed

Zhao, Ping; Xu, Ping; Li, Bingyan; Wang, Zhengrong

2003-09-01

This investigation was made to reveal the current status, research trend and research level of biomedical engineering in Chinese mainland by means of scientometrics and to assess the quality of the four domestic publications by bibliometrics. We identified all articles of four related publications by searching Chinese and foreign databases from 1997 to 2001. All articles collected or cited by these databases were searched and statistically analyzed for finding out the relevant distributions, including databases, years, authors, institutions, subject headings and subheadings. The source of sustentation funds and the related articles were analyzed too. The results showed that two journals were cited by two foreign databases and five Chinese databases simultaneously. The output of Journal of Biomedical Engineering was the highest. Its quantity of original papers cited by EI, CA and the totality of papers sponsored by funds were higher than those of the others, but the quantity and percentage per year of biomedical articles cited by EI were decreased in all. Inland core authors and institutions had come into being in the field of biomedical engineering. Their research topics were mainly concentrated on ten subject headings which included biocompatible materials, computer-assisted signal processing, electrocardiography, computer-assisted image processing, biomechanics, algorithms, electroencephalography, automatic data processing, mechanical stress, hemodynamics, mathematical computing, microcomputers, theoretical models, etc. The main subheadings were concentrated on instrumentation, physiopathology, diagnosis, therapy, ultrasonography, physiology, analysis, surgery, pathology, method, etc.

Flexible patient information search and retrieval framework: pilot implementation

NASA Astrophysics Data System (ADS)

Erdal, Selnur; Catalyurek, Umit V.; Saltz, Joel; Kamal, Jyoti; Gurcan, Metin N.

2007-03-01

Medical centers collect and store significant amount of valuable data pertaining to patients' visit in the form of medical free-text. In addition, standardized diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification: ICD9-CM) related to those dictated reports are usually available. In this work, we have created a framework where image searches could be initiated through a combination of free-text reports as well as ICD9 codes. This framework enables more comprehensive search on existing large sets of patient data in a systematic way. The free text search is enriched by computer-aided inclusion of additional search terms enhanced by a thesaurus. This combination of enriched search allows users to access to a larger set of relevant results from a patient-centric PACS in a simpler way. Therefore, such framework is of particular use in tasks such as gathering images for desired patient populations, building disease models, and so on. As the motivating application of our framework, we implemented a search engine. This search engine processed two years of patient data from the OSU Medical Center's Information Warehouse and identified lung nodule location information using a combination of UMLS Meta-Thesaurus enhanced text report searches along with ICD9 code searches on patients that have been discharged. Five different queries with various ICD9 codes involving lung cancer were carried out on 172552 cases. Each search was completed under a minute on average per ICD9 code and the inclusion of UMLS thesaurus increased the number of relevant cases by 45% on average.

Effects of Individual Health Topic Familiarity on Activity Patterns During Health Information Searches

PubMed Central

Moriyama, Koichi; Fukui, Ken–ichi; Numao, Masayuki

2015-01-01

Background Non-medical professionals (consumers) are increasingly using the Internet to support their health information needs. However, the cognitive effort required to perform health information searches is affected by the consumer’s familiarity with health topics. Consumers may have different levels of familiarity with individual health topics. This variation in familiarity may cause misunderstandings because the information presented by search engines may not be understood correctly by the consumers. Objective As a first step toward the improvement of the health information search process, we aimed to examine the effects of health topic familiarity on health information search behaviors by identifying the common search activity patterns exhibited by groups of consumers with different levels of familiarity. Methods Each participant completed a health terminology familiarity questionnaire and health information search tasks. The responses to the familiarity questionnaire were used to grade the familiarity of participants with predefined health topics. The search task data were transcribed into a sequence of search activities using a coding scheme. A computational model was constructed from the sequence data using a Markov chain model to identify the common search patterns in each familiarity group. Results Forty participants were classified into L1 (not familiar), L2 (somewhat familiar), and L3 (familiar) groups based on their questionnaire responses. They had different levels of familiarity with four health topics. The video data obtained from all of the participants were transcribed into 4595 search activities (mean 28.7, SD 23.27 per session). The most frequent search activities and transitions in all the familiarity groups were related to evaluations of the relevancy of selected web pages in the retrieval results. However, the next most frequent transitions differed in each group and a chi-squared test confirmed this finding (P<.001). Next, according to the

Concept recognition for extracting protein interaction relations from biomedical text

PubMed Central

Baumgartner, William A; Lu, Zhiyong; Johnson, Helen L; Caporaso, J Gregory; Paquette, Jesse; Lindemann, Anna; White, Elizabeth K; Medvedeva, Olga; Cohen, K Bretonnel; Hunter, Lawrence

2008-01-01

Background: Reliable information extraction applications have been a long sought goal of the biomedical text mining community, a goal that if reached would provide valuable tools to benchside biologists in their increasingly difficult task of assimilating the knowledge contained in the biomedical literature. We present an integrated approach to concept recognition in biomedical text. Concept recognition provides key information that has been largely missing from previous biomedical information extraction efforts, namely direct links to well defined knowledge resources that explicitly cement the concept's semantics. The BioCreative II tasks discussed in this special issue have provided a unique opportunity to demonstrate the effectiveness of concept recognition in the field of biomedical language processing. Results: Through the modular construction of a protein interaction relation extraction system, we present several use cases of concept recognition in biomedical text, and relate these use cases to potential uses by the benchside biologist. Conclusion: Current information extraction technologies are approaching performance standards at which concept recognition can begin to deliver high quality data to the benchside biologist. Our system is available as part of the BioCreative Meta-Server project and on the internet . PMID:18834500

Exploring antecedents of consumer satisfaction and repeated search behavior on e-health information.

PubMed

Lee, Yun Jung; Park, Jungkun; Widdows, Richard

2009-03-01

E-health information has become an important resource for people seeking health information. Even though many studies have been conducted to examine the quality of e-health information, only a few studies have explored the effects of the information seekers' motivations on the perceived quality of e-health information. There is even less information about repeated searches for e-health information after the users' initial experience of e-health information use. Using an online survey of information seekers, 252 e-health information users' responses were collected. The research examines the relationship among motivation, perceived quality, satisfaction, and intention to repeat-search e-health information. The results identify motivations to search e-health information and confirm the relationship among motivation, perceived quality dimensions, and satisfaction and intention to repeat searches for e-health information.

Searching the Polish Medical Bibliography (Polska Bibliografia Lekarska) for trials.

PubMed

Almerie, Muhammad Qutayba; Matar, Hosam El-Din; Jones, Vicki; Kumar, Ajit; Wright, Judith; Wlostowska, Ewa; Adams, Clive E

2007-12-01

The Polish Medical Bibliography (Polska Bibliografia Lekarska) contains 350 000 records dating from 1979. These records from the fields of medicine, nursing, dentistry, health care systems and preclinical sciences are from nearly 300 biomedical journals published in Poland. We systematically searched the Polish Medical Bibliography Part II (1996-2006) CD-ROM (July 2006) using both English and Polish phrases for randomized trials, manually checked results and, for the trials identified in this way, sought these on medline and embase. Systematic searching identified records of 680 randomized trials from all areas of health care. Nearly 40% of these were not found on either medline or embase. The Polish Medical Bibliography should be of interest to health care information specialists concerned with comprehensive searches for trials.

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

PubMed

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

Facilitating biomedical researchers' interrogation of electronic health record data: Ideas from outside of biomedical informatics.

PubMed

Hruby, Gregory W; Matsoukas, Konstantina; Cimino, James J; Weng, Chunhua

2016-04-01

Electronic health records (EHR) are a vital data resource for research uses, including cohort identification, phenotyping, pharmacovigilance, and public health surveillance. To realize the promise of EHR data for accelerating clinical research, it is imperative to enable efficient and autonomous EHR data interrogation by end users such as biomedical researchers. This paper surveys state-of-art approaches and key methodological considerations to this purpose. We adapted a previously published conceptual framework for interactive information retrieval, which defines three entities: user, channel, and source, by elaborating on channels for query formulation in the context of facilitating end users to interrogate EHR data. We show the current progress in biomedical informatics mainly lies in support for query execution and information modeling, primarily due to emphases on infrastructure development for data integration and data access via self-service query tools, but has neglected user support needed during iteratively query formulation processes, which can be costly and error-prone. In contrast, the information science literature has offered elaborate theories and methods for user modeling and query formulation support. The two bodies of literature are complementary, implying opportunities for cross-disciplinary idea exchange. On this basis, we outline the directions for future informatics research to improve our understanding of user needs and requirements for facilitating autonomous interrogation of EHR data by biomedical researchers. We suggest that cross-disciplinary translational research between biomedical informatics and information science can benefit our research in facilitating efficient data access in life sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Pathophysiologic mechanisms of biomedical nanomaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Liming, E-mail: wangliming@ihep.ac.cn; Chen, Chunying, E-mail: chenchy@nanoctr.cn

Nanomaterials (NMs) have been widespread used in biomedical fields, daily consuming, and even food industry. It is crucial to understand the safety and biomedical efficacy of NMs. In this review, we summarized the recent progress about the physiological and pathological effects of NMs from several levels: protein-nano interface, NM-subcellular structures, and cell–cell interaction. We focused on the detailed information of nano-bio interaction, especially about protein adsorption, intracellular trafficking, biological barriers, and signaling pathways as well as the associated mechanism mediated by nanomaterials. We also introduced related analytical methods that are meaningful and helpful for biomedical effect studies in the future.more » We believe that knowledge about pathophysiologic effects of NMs is not only significant for rational design of medical NMs but also helps predict their safety and further improve their applications in the future. - Highlights: • Rapid protein adsorption onto nanomaterials that affects biomedical effects • Nanomaterials and their interaction with biological membrane, intracellular trafficking and specific cellular effects • Nanomaterials and their interaction with biological barriers • The signaling pathways mediated by nanomaterials and related biomedical effects • Novel techniques for studying translocation and biomedical effects of NMs.« less

Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method.

PubMed

Liu, H; Lussier, Y A; Friedman, C

2001-08-01

With the growing use of Natural Language Processing (NLP) techniques for information extraction and concept indexing in the biomedical domain, a method that quickly and efficiently assigns the correct sense of an ambiguous biomedical term in a given context is needed concurrently. The current status of word sense disambiguation (WSD) in the biomedical domain is that handcrafted rules are used based on contextual material. The disadvantages of this approach are (i) generating WSD rules manually is a time-consuming and tedious task, (ii) maintenance of rule sets becomes increasingly difficult over time, and (iii) handcrafted rules are often incomplete and perform poorly in new domains comprised of specialized vocabularies and different genres of text. This paper presents a two-phase unsupervised method to build a WSD classifier for an ambiguous biomedical term W. The first phase automatically creates a sense-tagged corpus for W, and the second phase derives a classifier for W using the derived sense-tagged corpus as a training set. A formative experiment was performed, which demonstrated that classifiers trained on the derived sense-tagged corpora achieved an overall accuracy of about 97%, with greater than 90% accuracy for each individual ambiguous term.

A Study of the Information Search Behaviour of the Millennial Generation

ERIC Educational Resources Information Center

Taylor, Arthur

2012-01-01

Introduction: Members of the millennial generation (born after 1982) have come of age in a society infused with technology and information. It is unclear how they determine the validity of information gathered, or whether or not validity is even a concern. Previous information search models based on mediated searches with different age groups may…

View-Based Searching Systems--Progress Towards Effective Disintermediation.

ERIC Educational Resources Information Center

Pollitt, A. Steven; Smith, Martin P.; Treglown, Mark; Braekevelt, Patrick

This paper presents the background and then reports progress made in the development of two view-based searching systems--HIBROWSE for EMBASE, searching Europe's most important biomedical bibliographic database, and HIBROWSE for EPOQUE, improving access to the European Parliament's Online Query System. The HIBROWSE approach to searching promises…

Mining protein phosphorylation information from biomedical literature using NLP parsing and Support Vector Machines.

PubMed

Raja, Kalpana; Natarajan, Jeyakumar

2018-07-01

Extraction of protein phosphorylation information from biomedical literature has gained much attention because of the importance in numerous biological processes. In this study, we propose a text mining methodology which consists of two phases, NLP parsing and SVM classification to extract phosphorylation information from literature. First, using NLP parsing we divide the data into three base-forms depending on the biomedical entities related to phosphorylation and further classify into ten sub-forms based on their distribution with phosphorylation keyword. Next, we extract the phosphorylation entity singles/pairs/triplets and apply SVM to classify the extracted singles/pairs/triplets using a set of features applicable to each sub-form. The performance of our methodology was evaluated on three corpora namely PLC, iProLink and hPP corpus. We obtained promising results of >85% F-score on ten sub-forms of training datasets on cross validation test. Our system achieved overall F-score of 93.0% on iProLink and 96.3% on hPP corpus test datasets. Furthermore, our proposed system achieved best performance on cross corpus evaluation and outperformed the existing system with recall of 90.1%. The performance analysis of our unique system on three corpora reveals that it extracts protein phosphorylation information efficiently in both non-organism specific general datasets such as PLC and iProLink, and human specific dataset such as hPP corpus. Copyright © 2018 Elsevier B.V. All rights reserved.

What do web-use skill differences imply for online health information searches?

PubMed

Feufel, Markus A; Stahl, S Frederica

2012-06-13

Online health information is of variable and often low scientific quality. In particular, elderly less-educated populations are said to struggle in accessing quality online information (digital divide). Little is known about (1) how their online behavior differs from that of younger, more-educated, and more-frequent Web users, and (2) how the older population may be supported in accessing good-quality online health information. To specify the digital divide between skilled and less-skilled Web users, we assessed qualitative differences in technical skills, cognitive strategies, and attitudes toward online health information. Based on these findings, we identified educational and technological interventions to help Web users find and access good-quality online health information. We asked 22 native German-speaking adults to search for health information online. The skilled cohort consisted of 10 participants who were younger than 30 years of age, had a higher level of education, and were more experienced using the Web than 12 participants in the less-skilled cohort, who were at least 50 years of age. We observed online health information searches to specify differences in technical skills and analyzed concurrent verbal protocols to identify health information seekers' cognitive strategies and attitudes. Our main findings relate to (1) attitudes: health information seekers in both cohorts doubted the quality of information retrieved online; among poorly skilled seekers, this was mainly because they doubted their skills to navigate vast amounts of information; once a website was accessed, quality concerns disappeared in both cohorts, (2) technical skills: skilled Web users effectively filtered information according to search intentions and data sources; less-skilled users were easily distracted by unrelated information, and (3) cognitive strategies: skilled Web users searched to inform themselves; less-skilled users searched to confirm their health-related opinions

[Biomedical engineering today : An overview from the viewpoint of the German Biomedical Engineering Society].

PubMed

Schlötelburg, C; Becks, T; Stieglitz, T

2010-08-01

Biomedical engineering is characterized by the interdisciplinary co-operation of technology, science, and ways of thinking, probably more than any other technological area. The close interaction of engineering and information sciences with medicine and biology results in innovative products and methods, but also requires high standards for the interdisciplinary transfer of ideas into products for patients' benefits. This article describes the situation of biomedical engineering in Germany. It displays characteristics of the medical device industry and ranks it with respect to the international market. The research landscape is described as well as up-to-date research topics and trends. The national funding situation of research in biomedical engineering is reviewed and existing innovation barriers are discussed.

Architecture for biomedical multimedia information delivery on the World Wide Web

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Goh, Gin-Hua; Neve, Leif; Thoma, George R.

1997-10-01

Research engineers at the National Library of Medicine are building a prototype system for the delivery of multimedia biomedical information on the World Wide Web. This paper discuses the architecture and design considerations for the system, which will be used initially to make images and text from the third National Health and Nutrition Examination Survey (NHANES) publicly available. We categorized our analysis as follows: (1) fundamental software tools: we analyzed trade-offs among use of conventional HTML/CGI, X Window Broadway, and Java; (2) image delivery: we examined the use of unconventional TCP transmission methods; (3) database manager and database design: we discuss the capabilities and planned use of the Informix object-relational database manager and the planned schema for the HNANES database; (4) storage requirements for our Sun server; (5) user interface considerations; (6) the compatibility of the system with other standard research and analysis tools; (7) image display: we discuss considerations for consistent image display for end users. Finally, we discuss the scalability of the system in terms of incorporating larger or more databases of similar data, and the extendibility of the system for supporting content-based retrieval of biomedical images. The system prototype is called the Web-based Medical Information Retrieval System. An early version was built as a Java applet and tested on Unix, PC, and Macintosh platforms. This prototype used the MiniSQL database manager to do text queries on a small database of records of participants in the second NHANES survey. The full records and associated x-ray images were retrievable and displayable on a standard Web browser. A second version has now been built, also a Java applet, using the MySQL database manager.

Biomedical waste management in Ayurveda hospitals - current practices & future prospectives.

PubMed

Rajan, Renju; Robin, Delvin T; M, Vandanarani

2018-03-16

Biomedical waste management is an integral part of traditional and contemporary system of health care. The paper focuses on the identification and classification of biomedical wastes in Ayurvedic hospitals, current practices of its management in Ayurveda hospitals and its future prospective. Databases like PubMed (1975-2017 Feb), Scopus (1960-2017), AYUSH Portal, DOAJ, DHARA and Google scholar were searched. We used the medical subject headings 'biomedical waste' and 'health care waste' for identification and classification. The terms 'biomedical waste management', 'health care waste management' alone and combined with 'Ayurveda' or 'Ayurvedic' for current practices and recent advances in the treatment of these wastes were used. We made a humble attempt to categorize the biomedical wastes from Ayurvedic hospitals as the available data about its grouping is very scarce. Proper biomedical waste management is the mainstay of hospital cleanliness, hospital hygiene and maintenance activities. Current disposal techniques adopted for Ayurveda biomedical wastes are - sewage/drains, incineration and land fill. But these methods are having some merits as well as demerits. Our review has identified a number of interesting areas for future research such as the logical application of bioremediation techniques in biomedical waste management and the usage of effective micro-organisms and solar energy in waste disposal. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights reserved.

BEAUTY: an enhanced BLAST-based search tool that integrates multiple biological information resources into sequence similarity search results.

PubMed

Worley, K C; Wiese, B A; Smith, R F

1995-09-01

BEAUTY (BLAST enhanced alignment utility) is an enhanced version of the NCBI's BLAST data base search tool that facilitates identification of the functions of matched sequences. We have created new data bases of conserved regions and functional domains for protein sequences in NCBI's Entrez data base, and BEAUTY allows this information to be incorporated directly into BLAST search results. A Conserved Regions Data Base, containing the locations of conserved regions within Entrez protein sequences, was constructed by (1) clustering the entire data base into families, (2) aligning each family using our PIMA multiple sequence alignment program, and (3) scanning the multiple alignments to locate the conserved regions within each aligned sequence. A separate Annotated Domains Data Base was constructed by extracting the locations of all annotated domains and sites from sequences represented in the Entrez, PROSITE, BLOCKS, and PRINTS data bases. BEAUTY performs a BLAST search of those Entrez sequences with conserved regions and/or annotated domains. BEAUTY then uses the information from the Conserved Regions and Annotated Domains data bases to generate, for each matched sequence, a schematic display that allows one to directly compare the relative locations of (1) the conserved regions, (2) annotated domains and sites, and (3) the locally aligned regions matched in the BLAST search. In addition, BEAUTY search results include World-Wide Web hypertext links to a number of external data bases that provide a variety of additional types of information on the function of matched sequences. This convenient integration of protein families, conserved regions, annotated domains, alignment displays, and World-Wide Web resources greatly enhances the biological informativeness of sequence similarity searches. BEAUTY searches can be performed remotely on our system using the "BCM Search Launcher" World-Wide Web pages (URL is < http:/ /gc.bcm.tmc.edu:8088/ search-launcher/launcher.html > ).

United States National Library of Medicine Drug Information Portal.

PubMed

Hochstein, Colette; Goshorn, Jeanne; Chang, Florence

2009-01-01

The Drug Information Portal is a free Web resource from the National Library of Medicine (NLM) that provides a user-friendly gateway to current information for more than 15,000 drugs. The site guides users to related resources of NLM, the National Institutes of Health (NIH), and other government agencies. Current drug-related information regarding consumer health, clinical trials, AIDS, MeSH pharmacological actions, MEDLINE/PubMed biomedical literature, and physical properties and structure is easily retrieved by searching on a drug name. A varied selection of focused topics in medicine and drugs is also available from displayed subject headings. This column provides background information about the Drug Information Portal, as well as search basics.

Evaluation of research in biomedical ontologies

PubMed Central

Dumontier, Michel; Gkoutos, Georgios V.

2013-01-01

Ontologies are now pervasive in biomedicine, where they serve as a means to standardize terminology, to enable access to domain knowledge, to verify data consistency and to facilitate integrative analyses over heterogeneous biomedical data. For this purpose, research on biomedical ontologies applies theories and methods from diverse disciplines such as information management, knowledge representation, cognitive science, linguistics and philosophy. Depending on the desired applications in which ontologies are being applied, the evaluation of research in biomedical ontologies must follow different strategies. Here, we provide a classification of research problems in which ontologies are being applied, focusing on the use of ontologies in basic and translational research, and we demonstrate how research results in biomedical ontologies can be evaluated. The evaluation strategies depend on the desired application and measure the success of using an ontology for a particular biomedical problem. For many applications, the success can be quantified, thereby facilitating the objective evaluation and comparison of research in biomedical ontology. The objective, quantifiable comparison of research results based on scientific applications opens up the possibility for systematically improving the utility of ontologies in biomedical research. PMID:22962340

Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information and Social Tags on Information Search and Evaluation

PubMed Central

Oeberst, Aileen; Cress, Ulrike

2014-01-01

Background The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective. Objective The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts’ evaluations. Methods A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts’ blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants’ treatment recommendation after information search. Results Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t 173=7.67, P<.001, d=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F 2,168=10.61, P<.001, partial eta squared=0.112), blog post selection (F 2,168=6.55, P=.002, partial eta squared=0.072), and treatment efficacy ratings (F 2,168=8.48, P<.001, partial eta squared=0.092), compared

Medical and biomedical research productivity from Palestine, 2002 - 2011.

PubMed

Sweileh, Waleed M; Zyoud, Sa'ed H; Sawalha, Ansam F; Abu-Taha, Adham; Hussein, Ayman; Al-Jabi, Samah W

2013-02-02

Medical research productivity reflects the level of medical education and practice in a particular country. The objective of this study was to examine the quantity and quality of medical and biomedical research published from Palestine. Comprehensive review of the literature indexed by Scopus was conducted. Data from Jan 01, 2002 till December 31, 2011 was searched for authors affiliated with Palestine or Palestinian authority. Results were refined to limit the search to medical and biomedical subjects. The quality of publication was assessed using Journal Citation Report. The total number of publications was 2207. A total of 770 publications were in the medical and biomedical subject areas. The annual rate of publication was 0.077 articles per gross domestic product/capita. The 770 publications have an h-index of 32. One hundred and thirty eight (18%) articles were published in 46 journals that were not indexed in the web of knowledge. Twenty two (22/770; 2.9%) articles were published in journals with an IF > 10. The quantity and quality of research originating from Palestinian institutions is promising given the scarce resources of Palestine. However, more effort is needed to bridge the gap in medical research productivity and to promote better health in Palestine.

[Systematic literature search in PubMed : A short introduction].

PubMed

Blümle, A; Lagrèze, W A; Motschall, E

2018-03-01

In order to identify current (and relevant) evidence for a specific clinical question within the unmanageable amount of information available, solid skills in performing a systematic literature search are essential. An efficient approach is to search a biomedical database containing relevant literature citations of study reports. The best known database is MEDLINE, which is searchable for free via the PubMed interface. In this article, we explain step by step how to perform a systematic literature search via PubMed by means of an example research question in the field of ophthalmology. First, we demonstrate how to translate the clinical problem into a well-framed and searchable research question, how to identify relevant search terms and how to conduct a text word search and a search with keywords in medical subject headings (MeSH) terms. We then show how to limit the number of search results if the search yields too many irrelevant hits and how to increase the number in the case of too few citations. Finally, we summarize all essential principles that guide a literature search via PubMed.

An active visual search interface for Medline.

PubMed

Xuan, Weijian; Dai, Manhong; Mirel, Barbara; Wilson, Justin; Athey, Brian; Watson, Stanley J; Meng, Fan

2007-01-01

Searching the Medline database is almost a daily necessity for many biomedical researchers. However, available Medline search solutions are mainly designed for the quick retrieval of a small set of most relevant documents. Because of this search model, they are not suitable for the large-scale exploration of literature and the underlying biomedical conceptual relationships, which are common tasks in the age of high throughput experimental data analysis and cross-discipline research. We try to develop a new Medline exploration approach by incorporating interactive visualization together with powerful grouping, summary, sorting and active external content retrieval functions. Our solution, PubViz, is based on the FLEX platform designed for interactive web applications and its prototype is publicly available at: http://brainarray.mbni.med.umich.edu/Brainarray/DataMining/PubViz.

PubFocus: semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm

PubMed Central

Plikus, Maksim V; Zhang, Zina; Chuong, Cheng-Ming

2006-01-01

Background Understanding research activity within any given biomedical field is important. Search outputs generated by MEDLINE/PubMed are not well classified and require lengthy manual citation analysis. Automation of citation analytics can be very useful and timesaving for both novices and experts. Results PubFocus web server automates analysis of MEDLINE/PubMed search queries by enriching them with two widely used human factor-based bibliometric indicators of publication quality: journal impact factor and volume of forward references. In addition to providing basic volumetric statistics, PubFocus also prioritizes citations and evaluates authors' impact on the field of search. PubFocus also analyses presence and occurrence of biomedical key terms within citations by utilizing controlled vocabularies. Conclusion We have developed citations' prioritisation algorithm based on journal impact factor, forward referencing volume, referencing dynamics, and author's contribution level. It can be applied either to the primary set of PubMed search results or to the subsets of these results identified through key terms from controlled biomedical vocabularies and ontologies. NCI (National Cancer Institute) thesaurus and MGD (Mouse Genome Database) mammalian gene orthology have been implemented for key terms analytics. PubFocus provides a scalable platform for the integration of multiple available ontology databases. PubFocus analytics can be adapted for input sources of biomedical citations other than PubMed. PMID:17014720

A biomedical engineer's library.

PubMed

Webster, J G

1982-01-01

A survey resulted in a list of the 101 textbooks used by 62 biomedical engineering educational programs. A second list shows the textbooks used by each school. A third list shows the 27 textbooks used at two or more schools and the number of times each is used. This selected compilation should be useful to (a) biomedical engineering curriculum committees considering program revision, (b) teachers considering course revision, (c) university and industrial librarians updating their collections, (d) individuals building a personal library, and (e) students desiring information about the emphasis of various educational programs.

Biomedical Publishing and the Internet

PubMed Central

Jacobson, Michael W.

2000-01-01

The Internet is challenging traditional publishing patterns. In the biomedical domain, medical journals are providing more and more content online, both free and for a fee. Beyond this, however, a number of commentators believe that traditional notions of copyright and intellectual property ownership are no longer suited to the information age and that ownership of copyright to research reports should be and will be wrested from publishers and returned to authors. In this paper, it is argued that, although the Internet will indeed profoundly affect the distribution of biomedical research results, the biomedical publishing industry is too intertwined with the research establishment and too powerful to fall prey to such a copyright revolution. PMID:10833159

Do People Experience Cognitive Biases while Searching for Information?

PubMed Central

Lau, Annie Y.S.; Coiera, Enrico W.

2007-01-01

Objective To test whether individuals experience cognitive biases whilst searching using information retrieval systems. Biases investigated are anchoring, order, exposure and reinforcement. Design A retrospective analysis and a prospective experiment were conducted to investigate whether cognitive biases affect the way that documentary evidence is interpreted while searching online. The retrospective analysis was conducted on the search and decision behaviors of 75 clinicians (44 doctors, 31 nurses), answering questions for 8 clinical scenarios within 80 minutes in a controlled setting. The prospective study was conducted on 227 undergraduate students, who used the same search engine to answer two of six randomly assigned consumer health questions. Measurements Frequencies of correct answers pre- and post- search, and confidence in answers were collected. The impact of reading a document on the final decision was measured by the population likelihood ratio (LR) of the frequency of reading the document and the frequency of obtaining a correct answer. Documents with a LR > 1 were most likely to be associated with a correct answer, and those with a LR < 1 were most likely to be associated with an incorrect answer to a question. Agreement between a subject and the evidence they read was estimated by a concurrence rate, which measured the frequency that subjects’ answers agreed with the likelihood ratios of a group of documents, normalized for document order, time exposure or reinforcement through repeated access. Serial position curves were plotted for the relationship between subjects’ pre-search confidence, document order, the number of times and length of time a document was accessed, and concurrence with post-search answers. Chi-square analyses tested for the presence of biases, and the Kolmogorov-Smirnov test checked for equality of distribution of evidence in the comparison populations. Results A person’s prior belief (anchoring) has a significant impact on

Searching for evidence or approval? A commentary on database search in systematic reviews and alternative information retrieval methodologies.

PubMed

Delaney, Aogán; Tamás, Peter A

2018-03-01

Despite recognition that database search alone is inadequate even within the health sciences, it appears that reviewers in fields that have adopted systematic review are choosing to rely primarily, or only, on database search for information retrieval. This commentary reminds readers of factors that call into question the appropriateness of default reliance on database searches particularly as systematic review is adapted for use in new and lower consensus fields. It then discusses alternative methods for information retrieval that require development, formalisation, and evaluation. Our goals are to encourage reviewers to reflect critically and transparently on their choice of information retrieval methods and to encourage investment in research on alternatives. Copyright © 2017 John Wiley & Sons, Ltd.

Development and tuning of an original search engine for patent libraries in medicinal chemistry

PubMed Central

2014-01-01

Background The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. Methods We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. Results The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. Conclusions We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to

The Development of Information Search Expertise of Research Students

ERIC Educational Resources Information Center

Kai-Wah Chu, Samuel; Law, Nancy

2008-01-01

This study identifies the development of information search expertise of 12 beginning research students (six in education and six in engineering) who were provided with a set of systematic search training sessions over a period of one year. The study adopts a longitudinal approach in investigating whether there were different stages in the…

Education of biomedical engineering in Taiwan.

PubMed

Lin, Kang-Ping; Kao, Tsair; Wang, Jia-Jung; Chen, Mei-Jung; Su, Fong-Chin

2014-01-01

Biomedical Engineers (BME) play an important role in medical and healthcare society. Well educational programs are important to support the healthcare systems including hospitals, long term care organizations, manufacture industries of medical devices/instrumentations/systems, and sales/services companies of medical devices/instrumentations/system. In past 30 more years, biomedical engineering society has accumulated thousands people hold a biomedical engineering degree, and work as a biomedical engineer in Taiwan. Most of BME students can be trained in biomedical engineering departments with at least one of specialties in bioelectronics, bio-information, biomaterials or biomechanics. Students are required to have internship trainings in related institutions out of campus for 320 hours before graduating. Almost all the biomedical engineering departments are certified by IEET (Institute of Engineering Education Taiwan), and met the IEET requirement in which required mathematics and fundamental engineering courses. For BMEs after graduation, Taiwanese Society of Biomedical Engineering (TSBME) provides many continue-learning programs and certificates for all members who expect to hold the certification as a professional credit in his working place. In current status, many engineering departments in university are continuously asked to provide joint programs with BME department to train much better quality students. BME is one of growing fields in Taiwan.

Determining parents' patterns of behaviour when searching for online information on their child's health.

PubMed

Yardi, Shruti; Caldwell, Patrina Hy; Barnes, Elizabeth H; Scott, Karen M

2018-06-04

The internet has enabled parents to become informed medical consumers and take an active role in their child's treatment. We aimed to determine parents' online medical information-seeking behaviour about their child's health. This included sources of information, reasons for searching, use and assessment of information and whether parents wanted assistance with searching and assessing information. A questionnaire was distributed to 331 parents and carers of inpatients and outpatients at Children's Hospital at Westmead in 2015. Most questions involved tick-box responses and a few free-text responses. Responses were tabulated and described by frequencies and percentages. Associations between participant demographics and responses were examined using chi-square tests. In all, 308 (93%) questionnaires were returned. Most participants (90%) reported searching for medical information about their child's health. Of these, 96% searched the internet, and of these, 63% used a smartphone. The most common reason for searching before seeing the doctor was to prepare questions. The most common reasons for searching after seeing the doctor were to know more and because participants had more questions. Only half (57%) ascertained whether an information source was reliable. Most wanted guidance on searching (69%) and assessing reliability (77%). Almost all parents search for online information about their child's health, but most are unsure whether the information they find is trustworthy and are hesitant to act on or present it to their child's doctor. Health professionals could discuss this with parents during consultations to dispel potential misunderstandings and provide guidance on searching and assessing. © 2018 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Using Google Blogs and Discussions to Recommend Biomedical Resources: A Case Study

PubMed Central

Reed, Robyn B.; Chattopadhyay, Ansuman; Iwema, Carrie L.

2013-01-01

This case study investigated whether data gathered from discussions within the social media provide a reliable basis for a biomedical resources recommendation system. Using a search query to mine text from Google Blogs and Discussions, a ranking of biomedical resources was determined based on those most frequently mentioned. To establish quality, these results were compared to rankings by subject experts. An overall agreement between the frequency of social media discussions and subject expert recommendations was observed when identifying key bioinformatics and consumer health resources. Testing the method in more than one biomedical area implies this procedure could be employed across different subjects. PMID:24180648

The Aotus nancymaae erythrocyte proteome and its importance for biomedical research.

PubMed

Moreno-Pérez, D A; García-Valiente, R; Ibarrola, N; Muro, A; Patarroyo, M A

2017-01-30

The Aotus nancymaae species has been of great importance in researching the biology and pathogenesis of malaria, particularly for studying Plasmodium molecules for including them in effective vaccines against such microorganism. In spite of the forgoing, there has been no report to date describing the biology of parasite target cells in primates or their biomedical importance. This study was thus designed to analyse A. nancymaae erythrocyte protein composition using MS data collected during a previous study aimed at characterising the Plasmodium vivax proteome and published in the pertinent literature. Most peptides identified were similar to those belonging to 1189 Homo sapiens molecules; >95% of them had orthologues in New World primates. GO terms revealed a correlation between categories having the greatest amount of proteins and vital cell function. Integral membrane molecules were also identified which could be possible receptors facilitating interaction with Plasmodium species. The A. nancymaae erythrocyte proteome is described here for the first time, as a starting point for more in-depth/extensive studies. The data reported represents a source of invaluable information for laboratories interested in carrying out basic and applied biomedical investigation studies which involve using this primate. An understanding of the proteomics characteristics of A. nancymaae erythrocytes represents a fascinating area for research regarding the study of the pathogenesis of malaria since these are the main target for Plasmodium invasion. However, and even though Aotus is one of the non-human primate models considered most appropriate for biomedical research, knowledge of its proteome, particularly its erythrocytes, remains unknown. According to the above and bearing in mind the lack of information about the A. nancymaae species genome and transcriptome, this study involved a search for primate proteins for comparing their MS/MS spectra with the available information for

Issues in the design of a pilot concept-based query interface for the neuroinformatics information framework.

PubMed

Marenco, Luis; Li, Yuli; Martone, Maryann E; Sternberg, Paul W; Shepherd, Gordon M; Miller, Perry L

2008-09-01

This paper describes a pilot query interface that has been constructed to help us explore a "concept-based" approach for searching the Neuroscience Information Framework (NIF). The query interface is concept-based in the sense that the search terms submitted through the interface are selected from a standardized vocabulary of terms (concepts) that are structured in the form of an ontology. The NIF contains three primary resources: the NIF Resource Registry, the NIF Document Archive, and the NIF Database Mediator. These NIF resources are very different in their nature and therefore pose challenges when designing a single interface from which searches can be automatically launched against all three resources simultaneously. The paper first discusses briefly several background issues involving the use of standardized biomedical vocabularies in biomedical information retrieval, and then presents a detailed example that illustrates how the pilot concept-based query interface operates. The paper concludes by discussing certain lessons learned in the development of the current version of the interface.

Issues in the Design of a Pilot Concept-Based Query Interface for the Neuroinformatics Information Framework

PubMed Central

Li, Yuli; Martone, Maryann E.; Sternberg, Paul W.; Shepherd, Gordon M.; Miller, Perry L.

2009-01-01

This paper describes a pilot query interface that has been constructed to help us explore a “concept-based” approach for searching the Neuroscience Information Framework (NIF). The query interface is concept-based in the sense that the search terms submitted through the interface are selected from a standardized vocabulary of terms (concepts) that are structured in the form of an ontology. The NIF contains three primary resources: the NIF Resource Registry, the NIF Document Archive, and the NIF Database Mediator. These NIF resources are very different in their nature and therefore pose challenges when designing a single interface from which searches can be automatically launched against all three resources simultaneously. The paper first discusses briefly several background issues involving the use of standardized biomedical vocabularies in biomedical information retrieval, and then presents a detailed example that illustrates how the pilot concept-based query interface operates. The paper concludes by discussing certain lessons learned in the development of the current version of the interface. PMID:18953674

Opportunity for information search and the effect of false heart rate feedback.

PubMed

Barefoot, John C; Straub, Ronald B

2005-01-01

The role of information search in the attribution of physiological states was investigated by manipulating the subject's opportunity for information search following the presentation of false information about his heart-rate reactions to photographs of female nudes. Consistent with the self-persuasion hypothesis proposed by Valins, the rated attractiveness of the slides was not affected by the false heart-rate feedback for those subjects who were prevented from visually searching the slides. Those subjects who had ample opportunity to view the slides rated those slides accompanied by false information of a heart-rate change as more attractive than those slides which were not paired with a change in heart rate.

Next-Generation Search Engines for Information Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, Ranjeet; Hook, Leslie A; Palanisamy, Giri

centralized index. The harvested files are indexed against SOLR search API consistently, so that it can render search capabilities such as simple, fielded, spatial and temporal searches across a span of projects ranging from land, atmosphere, and ocean ecology. Mercury also provides data sharing capabilities using Open Archive Initiatives Protocol for Metadata Handling (OAI-PMH). In this paper we will discuss about the best practices for archiving data and metadata, new searching techniques, efficient ways of data retrieval and information display.« less

Geographical distribution of biomedical publications from the Gulf Corporation Council countries.

PubMed

Deleu, D; Northway, M G; Hanssens, Y

2001-01-01

It was our purpose to perform a geographical analysis for the number of biomedical and clinical research publications from the six countries of the Gulf Cooperation Council over the past decade (1990-1999). Medline was searched with the aid of the Internet provider PubMed. By using the advanced search option, entries were based on the country name for each of the Gulf Cooperation Council countries and the time period considered. The number of Medline-listed biomedical research papers published in the Gulf Cooperation Council countries over the last 10 years totaled 6,960 and increased by 14% over the past decade. The Kingdom of Saudi Arabia followed by Kuwait was by far the most prolific and accounted for 67 and 16% of publications. The research output from the United Arab Emirates and Oman grew steadily over the past decade, while it appeared to plateau for both Bahrain and Qatar. Taking into account that Gulf Cooperation Council countries have a relatively short history of research, the data show that the Gulf Cooperation Council countries are very prolific in terms of Medline-indexed biomedical research publications.

A biopsychosocial understanding of lower back pain: Content analysis of online information.

PubMed

Black, N M; Sullivan, S J; Mani, R

2018-04-01

(1) To develop a checklist to assess the representation of biopsychosocial lower back pain (LBP) online information; (2) to analyse publicly accessed online LBP information from a Google search for the degree that psychosocial contributors are described alongside the traditional biomedical approach to explaining LBP; (3) whether websites use information on pain biology to educate on LBP; (4) any inaccurate or false information regarding the mechanisms of LBP and; (5) the amount of websites certified by established benchmarks for quality health information. An online search was conducted using the Google search engines of six major English-speaking countries. Website content was analysed using three checklists developed for the purpose of this study - Biopsychosocial information categorisation checklist and scoring criteria; pain biology information checklist; and the inaccurate information checklist. Website quality was identified by the presence of an Health on the Net certification (HONcode). Of the fifteen websites analysed, the content of 26.7% of websites was classified as 'biomedical', 60% 'limited psychosocial' and 13.3% 'reasonable psychosocial'; 20% included information on pain biology; 46.7% inaccurately implied pain to be equal to tissue damage and 46.7% implied pathways specific to pain transmission; 40% were HONcode certified. Online LBP information retrieved through a Google search has limited to no integration of psychosocial or pain biology information. The focus on tissue pathology is further supported by the inaccurate descriptions of pain as equal to tissue damage and as an input to the central nervous system (CNS). Online LBP information needs to be guided by criteria more sensitive to the psychosocial contributors to pain. The online LBP information retrieved from a Google search needs to be guided by information more sensitive to the psychosocial contributors to pain and disability. This study also highlights the presence of inaccurate

Interpretation of the auto-mutual information rate of decrease in the context of biomedical signal analysis. Application to electroencephalogram recordings.

PubMed

Escudero, Javier; Hornero, Roberto; Abásolo, Daniel

2009-02-01

The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.

Medical and biomedical research productivity from Palestine, 2002 – 2011

PubMed Central

2013-01-01

Background Medical research productivity reflects the level of medical education and practice in a particular country. The objective of this study was to examine the quantity and quality of medical and biomedical research published from Palestine. Findings Comprehensive review of the literature indexed by Scopus was conducted. Data from Jan 01, 2002 till December 31, 2011 was searched for authors affiliated with Palestine or Palestinian authority. Results were refined to limit the search to medical and biomedical subjects. The quality of publication was assessed using Journal Citation Report. The total number of publications was 2207. A total of 770 publications were in the medical and biomedical subject areas. The annual rate of publication was 0.077 articles per gross domestic product/capita. The 770 publications have an h-index of 32. One hundred and thirty eight (18%) articles were published in 46 journals that were not indexed in the web of knowledge. Twenty two (22/770; 2.9%) articles were published in journals with an IF > 10. Conclusions The quantity and quality of research originating from Palestinian institutions is promising given the scarce resources of Palestine. However, more effort is needed to bridge the gap in medical research productivity and to promote better health in Palestine. PMID:23375070

NASA Biomedical Informatics Capabilities and Needs

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy A.

2009-01-01

To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

78 FR 13624 - Proposed Information Collection; Comment Request; Age Search Service

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-28

... Search Service AGENCY: U.S. Census Bureau, Commerce. ACTION: Notice. SUMMARY: The Department of Commerce...- 3434; or: [email protected] . SUPPLEMENTARY INFORMATION I. Abstract Age Search is a service... inheritance. The Age Search forms are used by the public in order to provide the Census Bureau with the...

75 FR 12174 - Proposed Information Collection; Comment Request; AGE Search Service

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-15

... DEPARTMENT OF COMMERCE Census Bureau Proposed Information Collection; Comment Request; AGE Search...: I. Abstract Age Search is a service provided by the U.S. Census Bureau for persons who need official... family relationship for rights of inheritance. The Age Search forms are used by the public in order to...

ON-LINE BIOMEDICAL DATABASES–THE BEST SOURCE FOR QUICK SEARCH OF THE SCIENTIFIC INFORMATION IN THE BIOMEDICINE

PubMed Central

Masic, Izet; Milinovic, Katarina

2012-01-01

Most of medical journals now has it’s electronic version, available over public networks. Although there are parallel printed and electronic versions, and one other form need not to be simultaneously published. Electronic version of a journal can be published a few weeks before the printed form and must not has identical content. Electronic form of a journals may have an extension that does not contain a printed form, such as animation, 3D display, etc., or may have available fulltext, mostly in PDF or XML format, or just the contents or a summary. Access to a full text is usually not free and can be achieved only if the institution (library or host) enters into an agreement on access. Many medical journals, however, provide free access for some articles, or after a certain time (after 6 months or a year) to complete content. The search for such journals provide the network archive as High Wire Press, Free Medical Journals.com. It is necessary to allocate PubMed and PubMed Central, the first public digital archives unlimited collect journals of available medical literature, which operates in the system of the National Library of Medicine in Bethesda (USA). There are so called on- line medical journals published only in electronic form. It could be searched over on-line databases. In this paper authors shortly described about 30 data bases and short instructions how to make access and search the published papers in indexed medical journals. PMID:23322957

DTMiner: identification of potential disease targets through biomedical literature mining

PubMed Central

Xu, Dong; Zhang, Meizhuo; Xie, Yanping; Wang, Fan; Chen, Ming; Zhu, Kenny Q.; Wei, Jia

2016-01-01

Motivation: Biomedical researchers often search through massive catalogues of literature to look for potential relationships between genes and diseases. Given the rapid growth of biomedical literature, automatic relation extraction, a crucial technology in biomedical literature mining, has shown great potential to support research of gene-related diseases. Existing work in this field has produced datasets that are limited both in scale and accuracy. Results: In this study, we propose a reliable and efficient framework that takes large biomedical literature repositories as inputs, identifies credible relationships between diseases and genes, and presents possible genes related to a given disease and possible diseases related to a given gene. The framework incorporates name entity recognition (NER), which identifies occurrences of genes and diseases in texts, association detection whereby we extract and evaluate features from gene–disease pairs, and ranking algorithms that estimate how closely the pairs are related. The F1-score of the NER phase is 0.87, which is higher than existing studies. The association detection phase takes drastically less time than previous work while maintaining a comparable F1-score of 0.86. The end-to-end result achieves a 0.259 F1-score for the top 50 genes associated with a disease, which performs better than previous work. In addition, we released a web service for public use of the dataset. Availability and Implementation: The implementation of the proposed algorithms is publicly available at http://gdr-web.rwebox.com/public_html/index.php?page=download.php. The web service is available at http://gdr-web.rwebox.com/public_html/index.php. Contact: jenny.wei@astrazeneca.com or kzhu@cs.sjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27506226

DTMiner: identification of potential disease targets through biomedical literature mining.

PubMed

Xu, Dong; Zhang, Meizhuo; Xie, Yanping; Wang, Fan; Chen, Ming; Zhu, Kenny Q; Wei, Jia

2016-12-01

Biomedical researchers often search through massive catalogues of literature to look for potential relationships between genes and diseases. Given the rapid growth of biomedical literature, automatic relation extraction, a crucial technology in biomedical literature mining, has shown great potential to support research of gene-related diseases. Existing work in this field has produced datasets that are limited both in scale and accuracy. In this study, we propose a reliable and efficient framework that takes large biomedical literature repositories as inputs, identifies credible relationships between diseases and genes, and presents possible genes related to a given disease and possible diseases related to a given gene. The framework incorporates name entity recognition (NER), which identifies occurrences of genes and diseases in texts, association detection whereby we extract and evaluate features from gene-disease pairs, and ranking algorithms that estimate how closely the pairs are related. The F1-score of the NER phase is 0.87, which is higher than existing studies. The association detection phase takes drastically less time than previous work while maintaining a comparable F1-score of 0.86. The end-to-end result achieves a 0.259 F1-score for the top 50 genes associated with a disease, which performs better than previous work. In addition, we released a web service for public use of the dataset. The implementation of the proposed algorithms is publicly available at http://gdr-web.rwebox.com/public_html/index.php?page=download.php The web service is available at http://gdr-web.rwebox.com/public_html/index.php CONTACT: jenny.wei@astrazeneca.com or kzhu@cs.sjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A negative trend of biomedical research in Libya: a bibliometric study.

PubMed

Benamer, Hani T S; Bredan, Amin; Bakoush, Omran

2009-09-01

It is well established that Libya is lagging behind its peers in biomedical research. The aim of this study is to analyse all the original biomedical publications affiliated with Libya from 1973 to 2007. PubMed and the Science Citation Index Expanded were searched for 'original research' biomedical studies affiliated with Libya. The generated data were hand searched and 329 'original research' studies were included in the analysis. The first study was published in 1973. Publication rate peaked to an average of 15.2 studies per year during 1986-1996 and dropped to an average of 8.8 studies per year during 1997-2007. Of 166 first authors; 41% were Libyans and 59% were expatriates. The latter contributed 104 studies between 1986 and 1996 and 36 studies between 1997 and 2007, while the Libyans contributed 63 and 61 studies in the two respective periods. Authors affiliated with Benghazi produced 67% of the published studies, while authors from Tripoli produced 30% and other medical schools, hospitals and research centres from other Libyan cities produced only 3%. This study showed a decline in biomedical research publication in Libya. We propose that the lack of a research culture among the Libyan medical professionals is one of the factors contributing to this decline, which coincided with the departure of expatriate doctors from Libya. Raising awareness of the importance of research and improving research skills among Libyan medical professionals may help to reverse the current trend.

Community outreach at biomedical research facilities.

PubMed

Goldman, M; Hedetniemi, J N; Herbert, E R; Sassaman, J S; Walker, B C

2000-12-01

For biomedical researchers to fulfill their responsibility for protecting the environment, they must do more than meet the scientific challenge of reducing the number and volume of hazardous materials used in their laboratories and the engineering challenge of reducing pollution and shifting to cleaner energy sources. They must also meet the public relations challenge of informing and involving their neighbors in these efforts. The experience of the Office of Community Liaison of the National Institutes of Health (NIH) in meeting the latter challenge offers a model and several valuable lessons for other biomedical research facilities to follow. This paper is based on presentations by an expert panel during the Leadership Conference on Biomedical Research and the Environment held 1--2 November 1999 at NIH, Bethesda, Maryland. The risks perceived by community members are often quite different from those identified by officials at the biomedical research facility. The best antidote for misconceptions is more and better information. If community organizations are to be informed participants in the decision-making process, they need a simple but robust mechanism for identifying and evaluating the environmental hazards in their community. Local government can and should be an active and fully informed partner in planning and emergency preparedness. In some cases this can reduce the regulatory burden on the biomedical research facility. In other cases it might simplify and expedite the permitting process or help the facility disseminate reliable information to the community. When a particular risk, real or perceived, is of special concern to the community, community members should be involved in the design, implementation, and evaluation of targeted risk assessment activities. Only by doing so will the community have confidence in the results of those activities. NIH has involved community members in joint efforts to deal with topics as varied as recycling and soil

Biomedical research and aerospace technology applications

NASA Technical Reports Server (NTRS)

1971-01-01

The accomplishments and activities of an Applications Team for biomedical subjects are presented. The team attempts to couple the technological problems and requirements in medicine with the relevant aerospace technology and, in particular, NASA-generated technology. The team actively engages in identifying these problems through direct contact with medical staffs or problem originators. The identification and specification of medical problems is followed by a search for technology which may be relevant to solutions to these problems.

Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags

NASA Astrophysics Data System (ADS)

Ohnishi, Kei; Yoshida, Kaori; Oie, Yuji

We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

A Systematic Understanding of Successful Web Searches in Information-Based Tasks

ERIC Educational Resources Information Center

Zhou, Mingming

2013-01-01

The purpose of this study is to research how Chinese university students solve information-based problems. With the Search Performance Index as the measure of search success, participants were divided into high, medium and low-performing groups. Based on their web search logs, these three groups were compared along five dimensions of the search…

Talk as a Metacognitive Strategy during the Information Search Process of Adolescents

ERIC Educational Resources Information Center

Bowler, Leanne

2010-01-01

Introduction: This paper describes a metacognitive strategy related to the social dimension of the information search process of adolescents. Method: A case study that used naturalistic methods to explore the metacognitive thinking nd associated emotions of ten adolescents. The study was framed by Kuhlthau's Information Search Process model and…

75 FR 67705 - Office of Postsecondary Education; Overview Information; Talent Search (TS) Program; Notice...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-03

... DEPARTMENT OF EDUCATION Office of Postsecondary Education; Overview Information; Talent Search (TS... currently being served by a Talent Search project, especially schools that the State has identified as the... reliable third-party sources when providing information on the implementation of their Talent Search...

Target-present guessing as a function of target prevalence and accumulated information in visual search.

PubMed

Peltier, Chad; Becker, Mark W

2017-05-01

Target prevalence influences visual search behavior. At low target prevalence, miss rates are high and false alarms are low, while the opposite is true at high prevalence. Several models of search aim to describe search behavior, one of which has been specifically intended to model search at varying prevalence levels. The multiple decision model (Wolfe & Van Wert, Current Biology, 20(2), 121--124, 2010) posits that all searches that end before the observer detects a target result in a target-absent response. However, researchers have found very high false alarms in high-prevalence searches, suggesting that prevalence rates may be used as a source of information to make "educated guesses" after search termination. Here, we further examine the ability for prevalence level and knowledge gained during visual search to influence guessing rates. We manipulate target prevalence and the amount of information that an observer accumulates about a search display prior to making a response to test if these sources of evidence are used to inform target present guess rates. We find that observers use both information about target prevalence rates and information about the proportion of the array inspected prior to making a response allowing them to make an informed and statistically driven guess about the target's presence.

Supporting undergraduate biomedical entrepreneurship.

PubMed

Patterson, P E

2004-01-01

As biomedical innovations become more sophisticated and expensive to bring to market, an approach is needed to ensure the survival of the best ideas. The tactic used by Iowa State University to provide entrepreneurship opportunities for undergraduate students in biomedical areas is a model that has proven to be both distinctive and effective. Iowa State supports and fosters undergraduate student entrepreneurship efforts through the Pappajohn Center for Entrepreneurship. This unique partnership encourages ISU faculty, researchers, and students to become involved in the world of entrepreneurship, while allowing Iowa's business communities to gain access to a wide array of available resources, skills, and information from Iowa State University.

Discovering and visualizing indirect associations between biomedical concepts

PubMed Central

Tsuruoka, Yoshimasa; Miwa, Makoto; Hamamoto, Kaisei; Tsujii, Jun'ichi; Ananiadou, Sophia

2011-01-01

Motivation: Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner. Results: This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance. Availability: FACTA+ is available as a web application at http://refine1-nactem.mc.man.ac.uk/facta/, and its visualizer is available at http://refine1-nactem.mc.man.ac.uk/facta-visualizer/. Contact: tsuruoka@jaist.ac.jp PMID:21685059

Lessons learned from a pilot implementation of the UMLS information sources map.

PubMed

Miller, P L; Frawley, S J; Wright, L; Roderer, N K; Powsner, S M

1995-01-01

To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question. A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source. The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration. An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this new environment, which are different

[Metrology research on biomedical engineering publications from China in recent years].

PubMed

Yu, Lu; Su, Juan; Wang, Ying; Sha, Xianzheng

2014-12-01

The present paper is to evaluate the scientific research level and development trends of biomedical engineering in China using metrology analysis on Chinese biomedical engineering scientific literatures. Pubmed is used to search the biomedical engineering publications in recent 5 years which are indexed by Science Citation Index, and the number and cited times of these publications and the impact factor of the journals are analyzed. The results show that comparing with the world, although the number of the publication in China has increased in recent 5 years, there is still much room for improvement. Among Chinese mainland, Hongkong and Taiwan, Chinese mainland maintains the obvious advantage in this subject, but Hongkong has the highest average cited number. Shanghai and Beijing have better research ability than other areas in Chinese mainland.

The role of information search in seeking alternative treatment for back pain: a qualitative analysis

PubMed Central

2014-01-01

Background Health consumers have moved away from a reliance on medical practitioner advice to more independent decision processes and so their information search processes have subsequently widened. This study examined how persons with back pain searched for alternative treatment types and service providers. That is, what information do they seek and how; what sources do they use and why; and by what means do they search for it? Methods 12 persons with back pain were interviewed. The method used was convergent interviewing. This involved a series of semi-structured questions to obtain open-ended answers. The interviewer analysed the responses and refined the questions after each interview, to converge on the dominant factors influencing decisions about treatment patterns. Results Persons with back pain mainly search their memories and use word of mouth (their doctor and friends) for information about potential treatments and service providers. Their search is generally limited due to personal, provider-related and information-supply reasons. However, they did want in-depth information about the alternative treatments and providers in an attempt to establish apriori their efficacy in treating their specific back problems. They searched different sources depending on the type of information they required. Conclusions The findings differ from previous studies about the types of information health consumers require when searching for information about alternative or mainstream healthcare services. The results have identified for the first time that limited information availability was only one of three categories of reasons identified about why persons with back pain do not search for more information particularly from external non-personal sources. PMID:24725300

Children's Search Engines from an Information Search Process Perspective.

ERIC Educational Resources Information Center

Broch, Elana

2000-01-01

Describes cognitive and affective characteristics of children and teenagers that may affect their Web searching behavior. Reviews literature on children's searching in online public access catalogs (OPACs) and using digital libraries. Profiles two Web search engines. Discusses some of the difficulties children have searching the Web, in the…

Roles and applications of biomedical ontologies in experimental animal science.

PubMed

Masuya, Hiroshi

2012-01-01

A huge amount of experimental data from past studies has played a vital role in the development of new knowledge and technologies in biomedical science. The importance of computational technologies for the reuse of data, data integration, and knowledge discoveries has also increased, providing means of processing large amounts of data. In recent years, information technologies related to "ontologies" have played more significant roles in the standardization, integration, and knowledge representation of biomedical information. This review paper outlines the history of data integration in biomedical science and its recent trends in relation to the field of experimental animal science.

Clique-based data mining for related genes in a biomedical database.

PubMed

Matsunaga, Tsutomu; Yonemori, Chikara; Tomita, Etsuji; Muramatsu, Masaaki

2009-07-01

Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph. We constructed a graph whose nodes were gene or disease pages, and edges were the hyperlink connections between those pages in the Online Mendelian Inheritance in Man (OMIM) database. We obtained over 20,000 sets of related genes (called 'gene modules') by enumerating cliques computationally. The modules included genes in the same family, genes for proteins that form a complex, and genes for components of the same signaling pathway. The results of experiments using 'metabolic syndrome'-related gene modules show that the gene modules can be used to get a coherent holistic picture helpful for interpreting relations among genes. We presented a data mining approach extracting related genes by enumerating cliques. The extracted gene sets provide a holistic picture useful for comprehending complex disease mechanisms.

[Big data, medical language and biomedical terminology systems].

PubMed

Schulz, Stefan; López-García, Pablo

2015-08-01

A variety of rich terminology systems, such as thesauri, classifications, nomenclatures and ontologies support information and knowledge processing in health care and biomedical research. Nevertheless, human language, manifested as individually written texts, persists as the primary carrier of information, in the description of disease courses or treatment episodes in electronic medical records, and in the description of biomedical research in scientific publications. In the context of the discussion about big data in biomedicine, we hypothesize that the abstraction of the individuality of natural language utterances into structured and semantically normalized information facilitates the use of statistical data analytics to distil new knowledge out of textual data from biomedical research and clinical routine. Computerized human language technologies are constantly evolving and are increasingly ready to annotate narratives with codes from biomedical terminology. However, this depends heavily on linguistic and terminological resources. The creation and maintenance of such resources is labor-intensive. Nevertheless, it is sensible to assume that big data methods can be used to support this process. Examples include the learning of hierarchical relationships, the grouping of synonymous terms into concepts and the disambiguation of homonyms. Although clear evidence is still lacking, the combination of natural language technologies, semantic resources, and big data analytics is promising.

Biomedical surface analysis: Evolution and future directions (Review)

PubMed Central

Castner, David G.

2017-01-01

This review describes some of the major advances made in biomedical surface analysis over the past 30–40 years. Starting from a single technique analysis of homogeneous surfaces, it has been developed into a complementary, multitechnique approach for obtaining detailed, comprehensive information about a wide range of surfaces and interfaces of interest to the biomedical community. Significant advances have been made in each surface analysis technique, as well as how the techniques are combined to provide detailed information about biological surfaces and interfaces. The driving force for these advances has been that the surface of a biomaterial is the interface between the biological environment and the biomaterial, and so, the state-of-the-art in instrumentation, experimental protocols, and data analysis methods need to be developed so that the detailed surface structure and composition of biomedical devices can be determined and related to their biological performance. Examples of these advances, as well as areas for future developments, are described for immobilized proteins, complex biomedical surfaces, nanoparticles, and 2D/3D imaging of biological materials. PMID:28438024

Biomedical semantics in the Semantic Web

PubMed Central

2011-01-01

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences? We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th. PMID:21388570

Biomedical semantics in the Semantic Web.

PubMed

Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

2011-03-07

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

BioSearch: a semantic search engine for Bio2RDF

PubMed Central

Qiu, Honglei; Huang, Jiacheng

2017-01-01

Abstract Biomedical data are growing at an incredible pace and require substantial expertise to organize data in a manner that makes them easily findable, accessible, interoperable and reusable. Massive effort has been devoted to using Semantic Web standards and technologies to create a network of Linked Data for the life sciences, among others. However, while these data are accessible through programmatic means, effective user interfaces for non-experts to SPARQL endpoints are few and far between. Contributing to user frustrations is that data are not necessarily described using common vocabularies, thereby making it difficult to aggregate results, especially when distributed across multiple SPARQL endpoints. We propose BioSearch — a semantic search engine that uses ontologies to enhance federated query construction and organize search results. BioSearch also features a simplified query interface that allows users to optionally filter their keywords according to classes, properties and datasets. User evaluation demonstrated that BioSearch is more effective and usable than two state of the art search and browsing solutions. Database URL: http://ws.nju.edu.cn/biosearch/ PMID:29220451

Internet use by the public to search for health-related information.

PubMed

AlGhamdi, Khalid M; Moussa, Noura A

2012-06-01

The use of the Internet to search for health-related information (HRI) has become a common practice worldwide. Our literature review failed to find any evidence of previous studies on this topic from Saudi Arabia. To determine the public use of the Internet in Saudi Arabia to search for HRI and to evaluate patients' perceptions of the quality of the information available on the Internet compared to that provided by their health care providers. A self-administered questionnaire about Internet use to search for HRI was distributed randomly to male and female outpatients and visitors attending a public University Hospital in Riyadh, Saudi Arabia from January to May 2010. A Chi-squared test was used to assess the association between different categorical variables. Multiple logistic regression was used to relate the use of the Internet to search for HRI with various socio-demographic variables. The questionnaire response was 80.1%, with completion of 801 of the 1000 distributed questionnaires; 50% (400/801) of respondents were males. The mean age of respondents was 32±11 years. The majority of respondents used the Internet in general (87.8%), and 58.4% of them (363/622) used the Internet to search for HRI. The majority stated a doctor was their primary source of HRI (89.3%, 654/732). This practice was considered useful by 84.2%, and the main reason behind it was sheer curiosity (92.7%, 418/451). Other reasons included not getting enough information from their doctor (58.5%, 227/413) and not trusting the information given by their doctor (28.2%, 101/443). Forty-four percent (205/466) searched for HRI before coming to the clinic; 72.5% of those discussed the information with their doctors and 71.7% (119/166) of those who did so believed that this positively affected their relationship with their doctor. Searching the Internet for health information was observed more frequently among the 30-39 year age group (OR=2.0, 95% CI 1.1-3.7), females (OR=3.8, 95% CI 2

Biomedical Big Data Training Collaborative (BBDTC): An effort to bridge the talent gap in biomedical science and research.

PubMed

Purawat, Shweta; Cowart, Charles; Amaro, Rommie E; Altintas, Ilkay

2017-05-01

The BBDTC (https://biobigdata.ucsd.edu) is a community-oriented platform to encourage high-quality knowledge dissemination with the aim of growing a well-informed biomedical big data community through collaborative efforts on training and education. The BBDTC is an e-learning platform that empowers the biomedical community to develop, launch and share open training materials. It deploys hands-on software training toolboxes through virtualization technologies such as Amazon EC2 and Virtualbox. The BBDTC facilitates migration of courses across other course management platforms. The framework encourages knowledge sharing and content personalization through the playlist functionality that enables unique learning experiences and accelerates information dissemination to a wider community.

Global polar geospatial information service retrieval based on search engine and ontology reasoning

USGS Publications Warehouse

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Do open access biomedical journals benefit smaller countries? The Slovenian experience.

PubMed

Turk, Nana

2011-06-01

Scientists from smaller countries have problems gaining visibility for their research. Does open access publishing provide a solution? Slovenia is a small country with around 5000 medical doctors, 1300 dentists and 1000 pharmacists. A search of Slovenia's Bibliographic database was carried out to identity all biomedical journals and those which are open access. Slovenia has 18 medical open access journals, but none has an impact factor and only 10 are indexed by Slovenian and international bibliographic databases. The visibility and quality of medical papers is poor. The solution might be to reduce the number of journals and encourage Slovenian scientists to publish their best articles in them. © 2011 The authors. Health Information and Libraries Journal © 2011 Health Libraries Group.

Finding Business Information on the "Invisible Web": Search Utilities vs. Conventional Search Engines.

ERIC Educational Resources Information Center

Darrah, Brenda

Researchers for small businesses, which may have no access to expensive databases or market research reports, must often rely on information found on the Internet, which can be difficult to find. Although current conventional Internet search engines are now able to index over on billion documents, there are many more documents existing in…

Integrating systems biology models and biomedical ontologies

PubMed Central

2011-01-01

Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028

KISTI at TREC 2014 Clinical Decision Support Track: Concept-based Document Re-ranking to Biomedical Information Retrieval

DTIC Science & Technology

2014-11-01

sematic type. Injury or Poisoning inpo T037 Anatomical Abnormality anab T190 Given a document D, a concept vector = {1, 2, … , ...integrating biomedical terminology . Nucleic acids research 32, Database issue (2004), 267–270. 5. Chapman, W.W., Hillert, D., Velupillai, S., et...Conference (TREC), (2011). 9. Koopman, B. and Zuccon, G. Understanding negation and family history to improve clinical information retrieval. Proceedings

Effects of technical editing in biomedical journals: a systematic review.

PubMed

Wager, Elizabeth; Middleton, Philippa

2002-06-05

Technical editing supposedly improves the accuracy and clarity of journal articles. We examined evidence of its effects on research reports in biomedical journals. Subset of a systematic review using Cochrane methods, searching MEDLINE, EMBASE, and other databases from earliest entries to February 2000 by using inclusive search terms; hand searching relevant journals. We selected comparative studies of the effects of editorial processes on original research articles between acceptance and publication in biomedical journals. Two reviewers assessed each study and performed independent data extraction. The 11 studies on technical editing indicate that it improves the readability of articles slightly (as measured by Gunning Fog and Flesch reading ease scores), may improve other aspects of their quality, can increase the accuracy of references and quotations, and raises the quality of abstracts. Supplying authors with abstract preparation instructions had no discernible effect. Considering the time and resources devoted to technical editing, remarkably little is know about its effects or the effects of imposing different house styles. Studies performed at 3 journals employing relatively large numbers of professional technical editors suggest that their editorial processes are associated with increases in readability and quality of articles, but these findings may not be generalizable to other journals.

Sources of Developmental Change in the Efficiency of Information Search

ERIC Educational Resources Information Center

Ruggeri, Azzurra; Lombrozo, Tania; Griffiths, Thomas L.; Xu, Fei

2016-01-01

Children are active learners: they learn not only from the information people offer and the evidence they happen to observe, but by actively seeking information. However, children's information search strategies are typically less efficient than those of adults. In two studies, we isolate potential sources of developmental change in how children…

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

PubMed

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

PATTERNS IN BIOMEDICAL DATA-HOW DO WE FIND THEM?

PubMed

Basile, Anna O; Verma, Anurag; Byrska-Bishop, Marta; Pendergrass, Sarah A; Darabos, Christian; Lester Kirchner, H

2017-01-01

Given the exponential growth of biomedical data, researchers are faced with numerous challenges in extracting and interpreting information from these large, high-dimensional, incomplete, and often noisy data. To facilitate addressing this growing concern, the "Patterns in Biomedical Data-How do we find them?" session of the 2017 Pacific Symposium on Biocomputing (PSB) is devoted to exploring pattern recognition using data-driven approaches for biomedical and precision medicine applications. The papers selected for this session focus on novel machine learning techniques as well as applications of established methods to heterogeneous data. We also feature manuscripts aimed at addressing the current challenges associated with the analysis of biomedical data.

Child Decision-Making: On the Burden of Predecisional Information Search

ERIC Educational Resources Information Center

Lindow, Stefanie; Betsch, Tilmann

2018-01-01

In many decision situations, individuals must actively search information before they can make a satisfying choice. In such instances, individuals must be aware of the fact that not all information may be equally relevant for the choice at hand--thus, individuals should weight information by its respective relevance. We compared children's and…

Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

Beyond PubMed: Searching the "Grey Literature" for Clinical Trial Results.

PubMed

Citrome, Leslie

2014-07-01

Clinical trial results have been traditionally communicated through the publication of scholarly reports and reviews in biomedical journals. However, this dissemination of information can be delayed or incomplete, making it difficult to appraise new treatments, or in the case of missing data, evaluate older interventions. Going beyond the routine search of PubMed, it is possible to discover additional information in the "grey literature." Examples of the grey literature include clinical trial registries, patent databases, company and industrywide repositories, regulatory agency digital archives, abstracts of paper and poster presentations on meeting/congress websites, industry investor reports and press releases, and institutional and personal websites.

Navigating the Path to a Biomedical Science Career

NASA Astrophysics Data System (ADS)

Zimmerman, Andrea McNeely

The number of biomedical PhD scientists being trained and graduated far exceeds the number of academic faculty positions and academic research jobs. If this trend is compelling biomedical PhD scientists to increasingly seek career paths outside of academia, then more should be known about their intentions, desires, training experiences, and career path navigation. Therefore, the purpose of this study was to understand the process through which biomedical PhD scientists are trained and supported for navigating future career paths. In addition, the study sought to determine whether career development support efforts and opportunities should be redesigned to account for the proportion of PhD scientists following non-academic career pathways. Guided by the social cognitive career theory (SCCT) framework this study sought to answer the following central research question: How does a southeastern tier 1 research university train and support its biomedical PhD scientists for navigating their career paths? Key findings are: Many factors influence PhD scientists' career sector preference and job search process, but the most influential were relationships with faculty, particularly the mentor advisor; Planned activities are a significant aspect of the training process and provide skills for career success; and Planned activities provided skills necessary for a career, but influential factors directed the career path navigated. Implications for practice and future research are discussed.

Trends in modeling Biomedical Complex Systems

PubMed Central

Milanesi, Luciano; Romano, Paolo; Castellani, Gastone; Remondini, Daniel; Liò, Petro

2009-01-01

In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented. PMID:19828068

Online games: a novel approach to explore how partial information influences human random searches

NASA Astrophysics Data System (ADS)

Martínez-García, Ricardo; Calabrese, Justin M.; López, Cristóbal

2017-01-01

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

Online games: a novel approach to explore how partial information influences human random searches.

PubMed

Martínez-García, Ricardo; Calabrese, Justin M; López, Cristóbal

2017-01-06

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

The SUNY biomedical communication network: six years of progress in on-line bibiographic retrieval.

PubMed Central

Egeland, J

1975-01-01

The SUNY Biomedical Communication Network became operational in 1968 as the first on-line bibliograhpic retrieval service for biomedical literature. Since 1968, the SUNY/BCN has grown in size from nine to thirty-two medical and university libraries and has expanded its data base coverage to include the ERIC and Psychological Abstracts data bases in addition to the full ten-year retrospective MEDLARS data base. Aside from the continuous provision of an on-line searching system, the SUNY experience over the last six years has yielded valuable information in the following areas of: (1) monograph indexing and retrieval, (2) shared cataloging, (3) user interaction and education in on-line systems, and (4) member participation in Network policy-making processes. The continued success of the SUNY/BCN is evidence that it is possible to provide a high quality on-line bibliographic retrieval system at cost to academic institutions. SUNY's success in this effort is the result of centralized resource sharing and effective regional networking, combined with thoughtful planning by user advisory committees. PMID:1173557

Retraction policies of high-impact biomedical journals

PubMed Central

Atlas, Michel C.

2004-01-01

Purpose: The purpose is to review the issue of retraction in the scientific literature and to examine the policies on retraction of major biomedical journals. Method: The historical background of this issue was investigated through a literature search. The Instructions to Authors of 122 major biomedical journals were reviewed for evidence of a policy on the retraction of articles. Editors of those journals with no mention of retraction in their Instructions to Authors were contacted by email and/or postal mail. Results: Sixty-two percent of the journals investigated did not post or report having a policy on issuing retractions. Only twenty-one (18%) did. The remainder did not post any policy and did not respond to inquiries. Discussion: Including policies in Instructions to Authors relating to the principled conduct of research and publication will improve the ethical environment in which the scientific community works. PMID:15098054

Introductory Course in Biomedical Ethics in the Obstetrics-Gynecology Residency.

ERIC Educational Resources Information Center

Elkins, Thomas E.

1988-01-01

Information used in a brief lecture that introduces a biomedical ethics curriculum in an obstetrics and gynecology residency is described. Major components include theories of philosophic ethics (formalist and consequentialist) and principles of biomedical ethics (honesty, contract-keeping, nonmaleficence, justice, autonomy, beneficence,…

Language Preferences on Websites and in Google Searches for Human Health and Food Information

PubMed Central

Singh, Punam Mony; Wight, Carly A; Sercinoglu, Olcan; Wilson, David C; Boytsov, Artem

2007-01-01

Background While it is known that the majority of pages on the World Wide Web are in English, little is known about the preferred language of users searching for health information online. Objectives (1) To help global and domestic publishers, for example health and food agencies, to determine the need for translation of online information from English into local languages. (2) To help these agencies determine which language(s) they should select when publishing information online in target nations and for target subpopulations within nations. Methods To estimate the percentage of Web publishers that translate their health and food websites, we measured the frequency at which domain names retrieved by Google overlap for language translations of the same health-related search term. To quantify language choice of searchers from different countries, Google provided estimates of the rate at which its search engine was queried in six languages relative to English for the terms “avian flu,” “tuberculosis,” “schizophrenia,” and “maize” (corn) from January 2004 to April 2006. The estimate was based on a 20% sample of all Google queries from 227 nations. Results We estimate that 80%-90% of health- and food-related institutions do not translate their websites into multiple languages, even when the information concerns pandemic disease such as avian influenza. Although Internet users are often well-educated, there was a strong preference for searching for health and food information in the local language, rather than English. For “avian flu,” we found that only 1% of searches in non-English-speaking nations were in English, whereas for “tuberculosis” or “schizophrenia,” about 4%-40% of searches in non-English countries employed English. A subset of searches for health information presumably originating from immigrants occurred in their native tongue, not the language of the adopted country. However, Spanish-language online searches for “avian flu

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

PubMed Central

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336

Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS.

PubMed

De-Arteaga, Maria; Eggel, Ivan; Do, Bao; Rubin, Daniel; Kahn, Charles E; Müller, Henning

2015-08-01

Information search has changed the way we manage knowledge and the ubiquity of information access has made search a frequent activity, whether via Internet search engines or increasingly via mobile devices. Medical information search is in this respect no different and much research has been devoted to analyzing the way in which physicians aim to access information. Medical image search is a much smaller domain but has gained much attention as it has different characteristics than search for text documents. While web search log files have been analysed many times to better understand user behaviour, the log files of hospital internal systems for search in a PACS/RIS (Picture Archival and Communication System, Radiology Information System) have rarely been analysed. Such a comparison between a hospital PACS/RIS search and a web system for searching images of the biomedical literature is the goal of this paper. Objectives are to identify similarities and differences in search behaviour of the two systems, which could then be used to optimize existing systems and build new search engines. Log files of the ARRS GoldMiner medical image search engine (freely accessible on the Internet) containing 222,005 queries, and log files of Stanford's internal PACS/RIS search called radTF containing 18,068 queries were analysed. Each query was preprocessed and all query terms were mapped to the RadLex (Radiology Lexicon) terminology, a comprehensive lexicon of radiology terms created and maintained by the Radiological Society of North America, so the semantic content in the queries and the links between terms could be analysed, and synonyms for the same concept could be detected. RadLex was mainly created for the use in radiology reports, to aid structured reporting and the preparation of educational material (Lanlotz, 2006) [1]. In standard medical vocabularies such as MeSH (Medical Subject Headings) and UMLS (Unified Medical Language System) specific terms of radiology are often

Information-seeking behaviour for epilepsy: an infodemiological study of searches for Wikipedia articles.

PubMed

Brigo, Francesco; Otte, Willem M; Igwe, Stanley C; Ausserer, Harald; Nardone, Raffaele; Tezzon, Frediano; Trinka, Eugen

2015-12-01

Millions of people worldwide use the internet daily as a source of health information. Wikipedia is a popular free online encyclopaedia used by patients and physicians to search for health-related information. Our aim was to evaluate information-seeking behaviour of English-speaking internet users searching Wikipedia for articles related to epilepsy and epileptic seizures. Using Wiki Trends, which provides quantitative information on daily viewing of articles, data on global search queries for Wikipedia articles related to epilepsy and seizures were analysed. The daily Wikipedia article views on syncope, psychogenic non-epileptic seizures, migraine, and multiple sclerosis served as comparative data. The period of analysis covered was from January 2008 to December 2014. Overall, the Wikipedia article "epilepsy and driving" was found to be more frequently visited than the articles "epilepsy and employment" or "epilepsy in children". Since January 2008, the Wikipedia article "multiple sclerosis" was more often visited compared to the articles "epilepsy", "syncope", "psychogenic non-epileptic seizures" or "migraine"; the article "epilepsy" ranked 3,779 and was less frequently visited than "multiple sclerosis", ranked at 571, in traffic on Wikipedia. The highest peak in search volume for the article "epilepsy" coincided with the news of a celebrity having seizures. Fears and worries about epileptic seizures, their impact on driving and employment, and news about celebrities with epilepsy might be major determinants in searching Wikipedia for information.

The Ontology for Biomedical Investigations.

PubMed

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

The Ontology for Biomedical Investigations

PubMed Central

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H.; Chibucos, Marcus C.; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A.; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L.; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A.; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H.; Schober, Daniel; Smith, Barry; Soldatova, Larisa N.; Stoeckert, Christian J.; Taylor, Chris F.; Torniai, Carlo; Turner, Jessica A.; Vita, Randi; Whetzel, Patricia L.; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

Switching health insurers: the role of price, quality and consumer information search.

PubMed

Boonen, Lieke H H M; Laske-Aldershof, Trea; Schut, Frederik T

2016-04-01

We examine the impact of price, service quality and information search on people's propensity to switch health insurers in the competitive Dutch health insurance market. Using panel data from annual household surveys and data on health insurers' premiums and quality ratings over the period 2006-2012, we estimate a random effects logit model of people's switching decisions. We find that switching propensities depend on health plan price and quality, and on people's age, health, education and having supplementary or group insurance. Young people (18-35 years) are more sensitive to price, whereas older people are more sensitive to quality. Searching for health plan information has a much stronger impact on peoples' sensitivity to price than to service quality. In addition, searching for health plan information has a stronger impact on the switching propensity of higher than lower educated people, suggesting that higher educated people make better use of available health plan information. Finally, having supplementary insurance significantly reduces older people's switching propensity.

Biomedical named entity extraction: some issues of corpus compatibilities.

PubMed

Ekbal, Asif; Saha, Sriparna; Sikdar, Utpal Kumar

2013-01-01

Named Entity (NE) extraction is one of the most fundamental and important tasks in biomedical information extraction. It involves identification of certain entities from text and their classification into some predefined categories. In the biomedical community, there is yet no general consensus regarding named entity (NE) annotation; thus, it is very difficult to compare the existing systems due to corpus incompatibilities. Due to this problem we can not also exploit the advantages of using different corpora together. In our present work we address the issues of corpus compatibilities, and use a single objective optimization (SOO) based classifier ensemble technique that uses the search capability of genetic algorithm (GA) for NE extraction in biomedicine. We hypothesize that the reliability of predictions of each classifier differs among the various output classes. We use Conditional Random Field (CRF) and Support Vector Machine (SVM) frameworks to build a number of models depending upon the various representations of the set of features and/or feature templates. It is to be noted that we tried to extract the features without using any deep domain knowledge and/or resources. In order to assess the challenges of corpus compatibilities, we experiment with the different benchmark datasets and their various combinations. Comparison results with the existing approaches prove the efficacy of the used technique. GA based ensemble achieves around 2% performance improvements over the individual classifiers. Degradation in performance on the integrated corpus clearly shows the difficulties of the task. In summary, our used ensemble based approach attains the state-of-the-art performance levels for entity extraction in three different kinds of biomedical datasets. The possible reasons behind the better performance in our used approach are the (i). use of variety and rich features as described in Subsection "Features for named entity extraction"; (ii) use of GA based

Personalisation of Generic Library Search Results Using Student Enrolment Information

ERIC Educational Resources Information Center

Alaofi, Marwah; Rumantir, Grace

2015-01-01

This research explores the application of implicit personalisation techniques in information retrieval in the context of education. Motivated by the large and ever-growing volume of resources in digital libraries, coupled with students' limited experience in searching for these resources, particularly in translating their information needs into…

Online Information Searches and Help Seeking for Mental Health Problems in Urban China.

PubMed

Chen, Juan; Zhu, Shizhan

2016-07-01

In recent years, the Internet has emerged as an alternative information source on mental health problems. Yet, the profile of the typical Internet help seeker is to be determined. Based on data from a household survey of 2558 Beijing residents, the study investigates online information searches and help seeking for mental health problems. Multinomial logistic regressions are estimated for respondents' access to the Internet, and mental-health-related information searches and help seeking on the Internet for the whole community sample and the most psychologically distressed subsample. The study identifies a digital divide in online help seeking for mental health issues based on age, migration and hukou status, and socio-economic factors. Youth and high socio-economic status are significant predictors of Internet access and use. Among the whole community sample, rural-to-urban migrants are less likely to have access to the Internet and search information or seek help online. Among the most psychologically distressed subsample, urban-to-urban migrants are significantly more likely to have access to the Internet and search information or seek help online. Given the shortage of mental health professionals in China, online information dissemination and guided self-help, if properly designed, could offer a means to reach large numbers of individuals in a cost-effective manner.

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

2017-04-01

In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

Search Algorithms as a Framework for the Optimization of Drug Combinations

PubMed Central

Coquin, Laurence; Schofield, Jennifer; Feala, Jacob D.; Reed, John C.; McCulloch, Andrew D.; Paternostro, Giovanni

2008-01-01

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms—originally developed for digital communication—modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs using only one-third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6–9 interventions in 80–90% of tests, compared with 15–30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution. PMID:19112483

Technology-induced errors. The current use of frameworks and models from the biomedical and life sciences literatures.

PubMed

Borycki, E M; Kushniruk, A W; Bellwood, P; Brender, J

2012-01-01

The objective of this paper is to examine the extent, range and scope to which frameworks, models and theories dealing with technology-induced error have arisen in the biomedical and life sciences literature as indexed by Medline®. To better understand the state of work in the area of technology-induced error involving frameworks, models and theories, the authors conducted a search of Medline® using selected key words identified from seminal articles in this research area. Articles were reviewed and those pertaining to frameworks, models or theories dealing with technology-induced error were further reviewed by two researchers. All articles from Medline® from its inception to April of 2011 were searched using the above outlined strategy. 239 citations were returned. Each of the abstracts for the 239 citations were reviewed by two researchers. Eleven articles met the criteria based on abstract review. These 11 articles were downloaded for further in-depth review. The majority of the articles obtained describe frameworks and models with reference to theories developed in other literatures outside of healthcare. The papers were grouped into several areas. It was found that articles drew mainly from three literatures: 1) the human factors literature (including human-computer interaction and cognition), 2) the organizational behavior/sociotechnical literature, and 3) the software engineering literature. A variety of frameworks and models were found in the biomedical and life sciences literatures. These frameworks and models drew upon and extended frameworks, models and theoretical perspectives that have emerged in other literatures. These frameworks and models are informing an emerging line of research in health and biomedical informatics involving technology-induced errors in healthcare.

Beyond PubMed: Searching the “Grey Literature” for Clinical Trial Results

PubMed Central

2014-01-01

Clinical trial results have been traditionally communicated through the publication of scholarly reports and reviews in biomedical journals. However, this dissemination of information can be delayed or incomplete, making it difficult to appraise new treatments, or in the case of missing data, evaluate older interventions. Going beyond the routine search of PubMed, it is possible to discover additional information in the “grey literature.” Examples of the grey literature include clinical trial registries, patent databases, company and industrywide repositories, regulatory agency digital archives, abstracts of paper and poster presentations on meeting/congress websites, industry investor reports and press releases, and institutional and personal websites. PMID:25337445

Searching for pain information, education, and support on the Internet.

PubMed

Colón, Yvette

2013-03-01

Questions from patients about pain conditions and analgesic pharmacotherapy and responses from authors are presented to help educate patients and make them more effective self-advocates. The topics addressed in this issue are searching for pain information, education, support, and providers on the Internet and evaluating online information.

A Personalised Information Support System for Searching Portals and E-Resources

ERIC Educational Resources Information Center

Sirisha, B. S.; Jeevan, V. K. J.; Raja Kumar, R. V.; Goswami, A.

2009-01-01

Purpose: The purpose of this paper is to describe the development of a personalised information support system to help faculty members to search various portals and e-resources without typing the search terms in different interfaces and to obtain results re-ordered without human intervention. Design/methodology/approach: After a careful survey of…

Extracting biomedical events from pairs of text entities

PubMed Central

2015-01-01

Background Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced queries of researchers and practitioners in biology, medicine, and related fields. Hence, the massive data flow calls for efficient automatic methods of text-mining that extract high-level information, such as biomedical events, from biomedical text. The usual computational tools of Natural Language Processing cannot be readily applied to extract these biomedical events, due to the peculiarities of the domain. Indeed, biomedical documents contain highly domain-specific jargon and syntax. These documents also describe distinctive dependencies, making text-mining in molecular biology a specific discipline. Results We address biomedical event extraction as the classification of pairs of text entities into the classes corresponding to event types. The candidate pairs of text entities are recursively provided to a multiclass classifier relying on Support Vector Machines. This recursive process extracts events involving other events as arguments. Compared to joint models based on Markov Random Fields, our model simplifies inference and hence requires shorter training and prediction times along with lower memory capacity. Compared to usual pipeline approaches, our model passes over a complex intermediate problem, while making a more extensive usage of sophisticated joint features between text entities. Our method focuses on the core event extraction of the Genia task of BioNLP challenges yielding the best result reported so far on the 2013 edition. PMID:26201478

Approaching the Affective Factors of Information Seeking: The Viewpoint of the Information Search Process Model

ERIC Educational Resources Information Center

Savolainen, Reijo

2015-01-01

Introduction: The article contributes to the conceptual studies of affective factors in information seeking by examining Kuhlthau's information search process model. Method: This random-digit dial telephone survey of 253 people (75% female) living in a rural, medically under-serviced area of Ontario, Canada, follows-up a previous interview study…

Biomedical research in a Digital Health Framework

PubMed Central

2014-01-01

This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements - data and tools - of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform. PMID:25472554

Compound image segmentation of published biomedical figures.

PubMed

Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

2018-04-01

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

Biomedical technology in Franconia.

PubMed

Efferth, T

2000-01-01

Medical instrumentation and biotechnology business is developing rapidly in Franconia. The universities of Bayreuth, Erlangen-Nürnberg, and Würzburg hold upper ranks in biomedical extramural funding research. They have a high competence in biomedical research, medical instrumentation, and biotechnology. The association "BioMedTec Franken e.V" has been founded at the beginning of 1999 both to foster the information exchange between universities, industry and politics and to facilitate the establishment of biomedical companies by means of science parks. In the IGZ (Innovation and Foundation Center Nürnberg-Fürth-Erlangen) 4,500 square meters of space are currently shared by 19 novel companies. Since 1985 60 companies in the IGZ had a total turnover of about 74 Mio Euro. The TGZ (Technologie- und Gründerzentrum) in Würzburg provides space for 11 companies. For the specific needs of biomedical technology companies further science parks will be set up in the near future. A science park for medical instrumentation will be founded in Erlangen (IZMP, Innovations- und Gründerzentrum für Medizintechnik und Pharma in der Region Nürnberg, Fürch, Erlangen). Furthermore, a Biomedical Technology Center and a Research Center for Bicompatible Materials are to be founded in Würzburg and Bayreuth, respectively. Several communication platforms (Bayern Innovativ, FORWISS, FTT, KIM, N-TEC-VISIT, TBU, WETTI etc.) allow the transfer of local academic research activities to industrial utilization and open new co-operation possibilities. International pharmaceutical companies (Novartis, Nürnberg; Pharmacia Upjohn, Erlangen) are located in Franconia. Central Franconia represents a national focus for medical instrumentation. The Erlangen settlement of the Medical Engineering Section of Siemens employs 4,500 people including approximately 1,000 employees in the Siemens research center.

Information Search as an Indication of Rationality in Student Choice of Higher Education

ERIC Educational Resources Information Center

Menon, Maria E.

2004-01-01

This paper investigates the degree of information search that precedes the choice of a private third-level educational institution in Cyprus. Information search is used as an indication of rationality in order to provide a test for the economic approach to the explanation of human behaviour. A survey was conducted among 120 college students in the…

Planning a new library in an age of transition: the Washington University School of Medicine Library and Biomedical Communications Center.

PubMed Central

Crawford, S; Halbrook, B

1990-01-01

In an era of great technological and socioeconomic changes, the Washington University School of Medicine conceptualized and built its first Library and Biomedical Communications Center in seventy-eight years. The planning process, evolution of the electronic library, and translation of functions into operating spaces are discussed. Since 1983, when the project was approved, a whole range of information technologies and services have emerged. The authors consider the kind of library that would operate in a setting where people can do their own searches, order data and materials through an electronic network, analyze and manage information, and use software to create their own publications. Images PMID:2393757

The caCORE Software Development Kit: Streamlining construction of interoperable biomedical information services

PubMed Central

Phillips, Joshua; Chilukuri, Ram; Fragoso, Gilberto; Warzel, Denise; Covitz, Peter A

2006-01-01

Background Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. Results The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key

The caCORE Software Development Kit: streamlining construction of interoperable biomedical information services.

PubMed

Phillips, Joshua; Chilukuri, Ram; Fragoso, Gilberto; Warzel, Denise; Covitz, Peter A

2006-01-06

Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for

Supervised Learning Based Hypothesis Generation from Biomedical Literature.

PubMed

Sang, Shengtian; Yang, Zhihao; Li, Zongyao; Lin, Hongfei

2015-01-01

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature. This approach splits the traditional processing of hypothesis generation with classic ABC model into AB model and BC model which are constructed with supervised learning method. Compared with the concept cooccurrence and grammar engineering-based approaches like SemRep, machine learning based models usually can achieve better performance in information extraction (IE) from texts. Then through combining the two models, the approach reconstructs the ABC model and generates biomedical hypotheses from literature. The experimental results on the three classic Swanson hypotheses show that our approach outperforms SemRep system.

Eventogram: A Visual Representation of Main Events in Biomedical Signals.

PubMed

Elgendi, Mohamed

2016-09-22

Biomedical signals carry valuable physiological information and many researchers have difficulty interpreting and analyzing long-term, one-dimensional, quasi-periodic biomedical signals. Traditionally, biomedical signals are analyzed and visualized using periodogram, spectrogram, and wavelet methods. However, these methods do not offer an informative visualization of main events within the processed signal. This paper attempts to provide an event-related framework to overcome the drawbacks of the traditional visualization methods and describe the main events within the biomedical signal in terms of duration and morphology. Electrocardiogram and photoplethysmogram signals are used in the analysis to demonstrate the differences between the traditional visualization methods, and their performance is compared against the proposed method, referred to as the " eventogram " in this paper. The proposed method is based on two event-related moving averages that visualizes the main time-domain events in the processed biomedical signals. The traditional visualization methods were unable to find dominant events in processed signals while the eventogram was able to visualize dominant events in signals in terms of duration and morphology. Moreover, eventogram -based detection algorithms succeeded with detecting main events in different biomedical signals with a sensitivity and positive predictivity >95%. The output of the eventogram captured unique patterns and signatures of physiological events, which could be used to visualize and identify abnormal waveforms in any quasi-periodic signal.

Beyond Search Technique and Strategy: Helping Students to Be Informed.

ERIC Educational Resources Information Center

Aversa, Elizabeth

1991-01-01

Suggests ways that the school library media specialist can help students become more successful as users of online information. Four types of barriers to becoming informed are described: (1) indicative access barriers (indexing systems and relevance); (2) physical access to documents identified in a search; (3) linguistic barriers; and (4)…

Biomedical data integration in computational drug design and bioinformatics.

PubMed

Seoane, Jose A; Aguiar-Pulido, Vanessa; Munteanu, Cristian R; Rivero, Daniel; Rabunal, Juan R; Dorado, Julian; Pazos, Alejandro

2013-03-01

In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.

Understanding vaccination resistance: vaccine search term selection bias and the valence of retrieved information.

PubMed

Ruiz, Jeanette B; Bell, Robert A

2014-10-07

Dubious vaccination-related information on the Internet leads some parents to opt out of vaccinating their children. To determine if negative, neutral and positive search terms retrieve vaccination information that differs in valence and confirms searchers' assumptions about vaccination. A content analysis of first-page Google search results was conducted using three negative, three neutral, and three positive search terms for the concepts "vaccine," "vaccination," and "MMR"; 84 of the 90 websites retrieved met inclusion requirements. Two coders independently and reliably coded for the presence or absence of each of 15 myths about vaccination (e.g., "vaccines cause autism"), statements that countered these myths, and recommendations for or against vaccination. Data were analyzed using descriptive statistics. Across all websites, at least one myth was perpetuated on 16.7% of websites and at least one myth was countered on 64.3% of websites. The mean number of myths perpetuated on websites retrieved with negative, neutral, and positive search terms, respectively, was 1.93, 0.53, and 0.40. The mean number of myths countered on websites retrieved with negative, neutral, and positive search terms, respectively, was 3.0, 3.27, and 2.87. Explicit recommendations regarding vaccination were offered on 22.6% of websites. A recommendation against vaccination was more often made on websites retrieved with negative search terms (37.5% of recommendations) than on websites retrieved with neutral (12.5%) or positive (0%) search terms. The concerned parent who seeks information about the risks of childhood immunizations will find more websites that perpetuate vaccine myths and recommend against vaccination than the parent who seeks information about the benefits of vaccination. This suggests that search term valence can lead to online information that supports concerned parents' misconceptions about vaccines. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sequencing actions: an information-search study of tradeoffs of priorities against spatiotemporal constraints.

PubMed

Gärling, T

1996-09-01

How people choose between sequences of actions was investigated in an everyday errand-planning task. In this task subjects chose the preferred sequence of performing a number of errands in a fictitious environment. Two experiments were conducted with undergraduate students serving as subjects. One group searched information about each alternative. The same information was directly available to another group. In Experiment 1 the results showed that for two errands subjects took into account all attributes describing the errands, thus suggesting a tradeoff between priority, wait time, and travel distance with priority being the most important. Consistent with this finding predominantly intraalternative information search was observed. These results were replicated in Experiment 2 for three errands. In addition choice outcomes, information search, and sequence of responding suggested that for more than two actions sequence choices are made in stages.

[The biomedical periodicals of Hungarian editions--historical overview].

PubMed

Berhidi, Anna; Geges, József; Vasas, Lívia

2006-03-12

The majority of Hungarian scientific results are published in international periodicals in foreign languages. Yet the publications in Hungarian scientific periodicals also should not be ignored. This study analyses biomedical periodicals of Hungarian edition from different points of view. Based on different databases a list of titles consisting of 119 items resulted, which contains both the core and the peripheral journals of the biomedical field. These periodicals were analysed empirically, one by one: checking out the titles. 13 of the titles are ceased, among the rest 106 Hungarian scientific journals 10 are published in English language. From the remaining majority of Hungarian language and publishing only a few show up in international databases. Although quarter of the Hungarian biomedical journals meet the requirements, which means they could be represented in international databases, these periodicals are not indexed. 42 biomedical periodicals are available online. Although quarter of these journals come with restricted access. 2/3 of the Hungarian biomedical journals have detailed instructions to authors. These instructions inform the publishing doctors and researchers of the requirements of a biomedical periodical. The increasing number of Hungarian biomedical journals published is welcome news. But it would be important for quality publications which are cited a lot to appear in the Hungarian journals. The more publications are cited, the more journals and authors gain in prestige on home and international level.

A modular framework for biomedical concept recognition

PubMed Central

2013-01-01

Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88

PubMed Phrases, an open set of coherent phrases for searching biomedical literature

PubMed Central

Kim, Sun; Yeganova, Lana; Comeau, Donald C.; Wilbur, W. John; Lu, Zhiyong

2018-01-01

In biomedicine, key concepts are often expressed by multiple words (e.g., ‘zinc finger protein’). Previous work has shown treating a sequence of words as a meaningful unit, where applicable, is not only important for human understanding but also beneficial for automatic information seeking. Here we present a collection of PubMed® Phrases that are beneficial for information retrieval and human comprehension. We define these phrases as coherent chunks that are logically connected. To collect the phrase set, we apply the hypergeometric test to detect segments of consecutive terms that are likely to appear together in PubMed. These text segments are then filtered using the BM25 ranking function to ensure that they are beneficial from an information retrieval perspective. Thus, we obtain a set of 705,915 PubMed Phrases. We evaluate the quality of the set by investigating PubMed user click data and manually annotating a sample of 500 randomly selected noun phrases. We also analyze and discuss the usage of these PubMed Phrases in literature search. PMID:29893755

Should biomedical research be like Airbnb?

PubMed

Bonazzi, Vivien R; Bourne, Philip E

2017-04-01

The thesis presented here is that biomedical research is based on the trusted exchange of services. That exchange would be conducted more efficiently if the trusted software platforms to exchange those services, if they exist, were more integrated. While simpler and narrower in scope than the services governing biomedical research, comparison to existing internet-based platforms, like Airbnb, can be informative. We illustrate how the analogy to internet-based platforms works and does not work and introduce The Commons, under active development at the National Institutes of Health (NIH) and elsewhere, as an example of the move towards platforms for research.

Should biomedical research be like Airbnb?

PubMed Central

Bonazzi, Vivien R.

2017-01-01

The thesis presented here is that biomedical research is based on the trusted exchange of services. That exchange would be conducted more efficiently if the trusted software platforms to exchange those services, if they exist, were more integrated. While simpler and narrower in scope than the services governing biomedical research, comparison to existing internet-based platforms, like Airbnb, can be informative. We illustrate how the analogy to internet-based platforms works and does not work and introduce The Commons, under active development at the National Institutes of Health (NIH) and elsewhere, as an example of the move towards platforms for research. PMID:28388615

State of reporting of primary biomedical research: a scoping review protocol

PubMed Central

Mbuagbaw, Lawrence; Samaan, Zainab; Jin, Yanling; Nwosu, Ikunna; Levine, Mitchell A H; Adachi, Jonathan D; Thabane, Lehana

2017-01-01

Introduction Incomplete or inconsistent reporting remains a major concern in the biomedical literature. Incomplete or inconsistent reporting may yield the published findings unreliable, irreproducible or sometimes misleading. In this study based on evidence from systematic reviews and surveys that have evaluated the reporting issues in primary biomedical studies, we aim to conduct a scoping review with focuses on (1) the state-of-the-art extent of adherence to the emerging reporting guidelines in primary biomedical research, (2) the inconsistency between protocols or registrations and full reports and (3) the disagreement between abstracts and full-text articles. Methods and analyses We will use a comprehensive search strategy to retrieve all available and eligible systematic reviews and surveys in the literature. We will search the following electronic databases: Web of Science, Excerpta Medica Database (EMBASE), MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Our outcomes are levels of adherence to reporting guidelines, levels of consistency between protocols or registrations and full reports and the agreement between abstracts and full reports, all of which will be expressed as percentages, quality scores or categorised rating (such as high, medium and low). No pooled analyses will be performed quantitatively given the heterogeneity of the included systematic reviews and surveys. Likewise, factors associated with improved completeness and consistency of reporting will be summarised qualitatively. The quality of the included systematic reviews will be evaluated using AMSTAR (a measurement tool to assess systematic reviews). Ethics and dissemination All findings will be published in peer-reviewed journals and relevant conferences. These results may advance our understanding of the extent of incomplete and inconsistent reporting, factors related to improved completeness and consistency of reporting and potential recommendations for

For 481 biomedical open access journals, articles are not searchable in the Directory of Open Access Journals nor in conventional biomedical databases

PubMed Central

Andresen, Kristoffer; Pommergaard, Hans-Christian; Rosenberg, Jacob

2015-01-01

Background. Open access (OA) journals allows access to research papers free of charge to the reader. Traditionally, biomedical researchers use databases like MEDLINE and EMBASE to discover new advances. However, biomedical OA journals might not fulfill such databases’ criteria, hindering dissemination. The Directory of Open Access Journals (DOAJ) is a database exclusively listing OA journals. The aim of this study was to investigate DOAJ’s coverage of biomedical OA journals compared with the conventional biomedical databases. Methods. Information on all journals listed in four conventional biomedical databases (MEDLINE, PubMed Central, EMBASE and SCOPUS) and DOAJ were gathered. Journals were included if they were (1) actively publishing, (2) full OA, (3) prospectively indexed in one or more database, and (4) of biomedical subject. Impact factor and journal language were also collected. DOAJ was compared with conventional databases regarding the proportion of journals covered, along with their impact factor and publishing language. The proportion of journals with articles indexed by DOAJ was determined. Results. In total, 3,236 biomedical OA journals were included in the study. Of the included journals, 86.7% were listed in DOAJ. Combined, the conventional biomedical databases listed 75.0% of the journals; 18.7% in MEDLINE; 36.5% in PubMed Central; 51.5% in SCOPUS and 50.6% in EMBASE. Of the journals in DOAJ, 88.7% published in English and 20.6% had received impact factor for 2012 compared with 93.5% and 26.0%, respectively, for journals in the conventional biomedical databases. A subset of 51.1% and 48.5% of the journals in DOAJ had articles indexed from 2012 and 2013, respectively. Of journals exclusively listed in DOAJ, one journal had received an impact factor for 2012, and 59.6% of the journals had no content from 2013 indexed in DOAJ. Conclusions. DOAJ is the most complete registry of biomedical OA journals compared with five conventional biomedical

For 481 biomedical open access journals, articles are not searchable in the Directory of Open Access Journals nor in conventional biomedical databases.

PubMed

Liljekvist, Mads Svane; Andresen, Kristoffer; Pommergaard, Hans-Christian; Rosenberg, Jacob

2015-01-01

Background. Open access (OA) journals allows access to research papers free of charge to the reader. Traditionally, biomedical researchers use databases like MEDLINE and EMBASE to discover new advances. However, biomedical OA journals might not fulfill such databases' criteria, hindering dissemination. The Directory of Open Access Journals (DOAJ) is a database exclusively listing OA journals. The aim of this study was to investigate DOAJ's coverage of biomedical OA journals compared with the conventional biomedical databases. Methods. Information on all journals listed in four conventional biomedical databases (MEDLINE, PubMed Central, EMBASE and SCOPUS) and DOAJ were gathered. Journals were included if they were (1) actively publishing, (2) full OA, (3) prospectively indexed in one or more database, and (4) of biomedical subject. Impact factor and journal language were also collected. DOAJ was compared with conventional databases regarding the proportion of journals covered, along with their impact factor and publishing language. The proportion of journals with articles indexed by DOAJ was determined. Results. In total, 3,236 biomedical OA journals were included in the study. Of the included journals, 86.7% were listed in DOAJ. Combined, the conventional biomedical databases listed 75.0% of the journals; 18.7% in MEDLINE; 36.5% in PubMed Central; 51.5% in SCOPUS and 50.6% in EMBASE. Of the journals in DOAJ, 88.7% published in English and 20.6% had received impact factor for 2012 compared with 93.5% and 26.0%, respectively, for journals in the conventional biomedical databases. A subset of 51.1% and 48.5% of the journals in DOAJ had articles indexed from 2012 and 2013, respectively. Of journals exclusively listed in DOAJ, one journal had received an impact factor for 2012, and 59.6% of the journals had no content from 2013 indexed in DOAJ. Conclusions. DOAJ is the most complete registry of biomedical OA journals compared with five conventional biomedical databases

Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery

PubMed Central

van Haagen, Herman H. H. B. M.; 't Hoen, Peter A. C.; Mons, Barend; Schultes, Erik A.

2013-01-01

Motivation Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins) others generic (e.g., ‘Homo sapiens’). Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI) by filtering generic concepts (node filtering) or links to generic concepts (edge filtering) from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering), and assessed the retrieval performance of networks composed of generic information alone. Results Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept “binding” is indicative for PPI retrieval and the concept “mutation abnormality” is

Constructing Uniform Resource Locators (URLs) for Searching the Marine Realms Information Bank

USGS Publications Warehouse

Linck, Guthrie A.; Allwardt, Alan O.; Lightsom, Frances L.

2009-01-01

The Marine Realms Information Bank (MRIB) is a digital library that provides access to free online scientific information about the oceans and coastal regions. To search its collection, MRIB uses a Common Gateway Interface (CGI) program, which allows automated search requests using Uniform Resource Locators (URLs). This document provides an overview of how to construct URLs to execute MRIB queries. The parameters listed allow detailed control of which records are retrieved, how they are returned, and how their display is formatted.

Applications of Ontology Design Patterns in Biomedical Ontologies

PubMed Central

Mortensen, Jonathan M.; Horridge, Matthew; Musen, Mark A.; Noy, Natalya F.

2012-01-01

Ontology design patterns (ODPs) are a proposed solution to facilitate ontology development, and to help users avoid some of the most frequent modeling mistakes. ODPs originate from similar approaches in software engineering, where software design patterns have become a critical aspect of software development. There is little empirical evidence for ODP prevalence or effectiveness thus far. In this work, we determine the use and applicability of ODPs in a case study of biomedical ontologies. We encoded ontology design patterns from two ODP catalogs. We then searched for these patterns in a set of eight ontologies. We found five patterns of the 69 patterns. Two of the eight ontologies contained these patterns. While ontology design patterns provide a vehicle for capturing formally reoccurring models and best practices in ontology design, we show that today their use in a case study of widely used biomedical ontologies is limited. PMID:23304337

The Biomedical Resource Ontology (BRO) to Enable Resource Discovery in Clinical and Translational Research

PubMed Central

Tenenbaum, Jessica D.; Whetzel, Patricia L.; Anderson, Kent; Borromeo, Charles D.; Dinov, Ivo D.; Gabriel, Davera; Kirschner, Beth; Mirel, Barbara; Morris, Tim; Noy, Natasha; Nyulas, Csongor; Rubenson, David; Saxman, Paul R.; Singh, Harpreet; Whelan, Nancy; Wright, Zach; Athey, Brian D.; Becich, Michael J.; Ginsburg, Geoffrey S.; Musen, Mark A.; Smith, Kevin A.; Tarantal, Alice F.; Rubin, Daniel L; Lyster, Peter

2010-01-01

The biomedical research community relies on a diverse set of resources, both within their own institutions and at other research centers. In addition, an increasing number of shared electronic resources have been developed. Without effective means to locate and query these resources, it is challenging, if not impossible, for investigators to be aware of the myriad resources available, or to effectively perform resource discovery when the need arises. In this paper, we describe the development and use of the Biomedical Resource Ontology (BRO) to enable semantic annotation and discovery of biomedical resources. We also describe the Resource Discovery System (RDS) which is a federated, inter-institutional pilot project that uses the BRO to facilitate resource discovery on the Internet. Through the RDS framework and its associated Biositemaps infrastructure, the BRO facilitates semantic search and discovery of biomedical resources, breaking down barriers and streamlining scientific research that will improve human health. PMID:20955817

Biomedical publishing and the internet: evolution or revolution?

PubMed

Jacobson, M W

2000-01-01

The Internet is challenging traditional publishing patterns. In the biomedical domain, medical journals are providing more and more content online, both free and for a fee. Beyond this, however, a number of commentators believe that traditional notions of copyright and intellectual property ownership are no longer suited to the information age and that ownership of copyright to research reports should be and will be wrested from publishers and returned to authors. In this paper, it is argued that, although the Internet will indeed profoundly affect the distribution of biomedical research results, the biomedical publishing industry is too intertwined with the research establishment and too powerful to fall prey to such a copyright revolution.

Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research.

PubMed

Bowen, Anthony; Casadevall, Arturo

2015-09-08

Society makes substantial investments in biomedical research, searching for ways to better human health. The product of this research is principally information published in scientific journals. Continued investment in science relies on society's confidence in the accuracy, honesty, and utility of research results. A recent focus on productivity has dominated the competitive evaluation of scientists, creating incentives to maximize publication numbers, citation counts, and publications in high-impact journals. Some studies have also suggested a decreasing quality in the published literature. The efficiency of society's investments in biomedical research, in terms of improved health outcomes, has not been studied. We show that biomedical research outcomes over the last five decades, as estimated by both life expectancy and New Molecular Entities approved by the Food and Drug Administration, have remained relatively constant despite rising resource inputs and scientific knowledge. Research investments by the National Institutes of Health over this time correlate with publication and author numbers but not with the numerical development of novel therapeutics. We consider several possibilities for the growing input-outcome disparity including the prior elimination of easier research questions, increasing specialization, overreliance on reductionism, a disproportionate emphasis on scientific outputs, and other negative pressures on the scientific enterprise. Monitoring the efficiency of research investments in producing positive societal outcomes may be a useful mechanism for weighing the efficacy of reforms to the scientific enterprise. Understanding the causes of the increasing input-outcome disparity in biomedical research may improve society's confidence in science and provide support for growing future research investments.

Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research

PubMed Central

Bowen, Anthony; Casadevall, Arturo

2015-01-01

Society makes substantial investments in biomedical research, searching for ways to better human health. The product of this research is principally information published in scientific journals. Continued investment in science relies on society’s confidence in the accuracy, honesty, and utility of research results. A recent focus on productivity has dominated the competitive evaluation of scientists, creating incentives to maximize publication numbers, citation counts, and publications in high-impact journals. Some studies have also suggested a decreasing quality in the published literature. The efficiency of society’s investments in biomedical research, in terms of improved health outcomes, has not been studied. We show that biomedical research outcomes over the last five decades, as estimated by both life expectancy and New Molecular Entities approved by the Food and Drug Administration, have remained relatively constant despite rising resource inputs and scientific knowledge. Research investments by the National Institutes of Health over this time correlate with publication and author numbers but not with the numerical development of novel therapeutics. We consider several possibilities for the growing input-outcome disparity including the prior elimination of easier research questions, increasing specialization, overreliance on reductionism, a disproportionate emphasis on scientific outputs, and other negative pressures on the scientific enterprise. Monitoring the efficiency of research investments in producing positive societal outcomes may be a useful mechanism for weighing the efficacy of reforms to the scientific enterprise. Understanding the causes of the increasing input-outcome disparity in biomedical research may improve society’s confidence in science and provide support for growing future research investments. PMID:26283360

Biomedical informatics training at the University of Wisconsin-Madison.

PubMed

Severtson, D J; Pape, L; Page, C D; Shavlik, J W; Phillips, G N; Flatley Brennan, P

2007-01-01

The purpose of this paper is to describe biomedical informatics training at the University of Wisconsin-Madison (UW-Madison). We reviewed biomedical informatics training, research, and faculty/trainee participation at UW-Madison. There are three primary approaches to training 1) The Computation & Informatics in Biology & Medicine Training Program, 2) formal biomedical informatics offered by various campus departments, and 3) individualized programs. Training at UW-Madison embodies the features of effective biomedical informatics training recommended by the American College of Medical Informatics that were delineated as: 1) curricula that integrate experiences among computational sciences and application domains, 2) individualized and interdisciplinary cross-training among a diverse cadre of trainees to develop key competencies that he or she does not initially possess, 3) participation in research and development activities, and 4) exposure to a range of basic informational and computational sciences. The three biomedical informatics training approaches immerse students in multidisciplinary training and education that is supported by faculty trainers who participate in collaborative research across departments. Training is provided across a range of disciplines and available at different training stages. Biomedical informatics training at UW-Madison illustrates how a large research University, with multiple departments across biological, computational and health fields, can provide effective and productive biomedical informatics training via multiple bioinformatics training approaches.

Empowering Students to Make Sense of an Information-Saturated World: The Evolution of "Information Searching and Analysis"

ERIC Educational Resources Information Center

Wittebols, James H.

2016-01-01

How well students conduct research online is an increasing concern for educators at all levels, especially higher education. This paper describes the evolution of a course that examines confirmation bias, information searching, and the political economy of information as keys to becoming more information and media literate. After a key assignment…

Information search in health care decision-making: a study of word-of-mouth and internet information users.

PubMed

Snipes, Robin L; Ingram, Rhea; Jiang, Pingjun

2005-01-01

This paper investigates how individual consumers may differ in their information search behavior in health care decision-making. Results indicate that most consumers still use word-of-mouth as a primary information source for health care decisions. However, usage of the Internet is increasing. The results of this study indicate that consumers who are most likely to use the Internet for health care information are single, younger, and less educated, whereas consumers who are most likely to use word-of-mouth are middle-aged, married, with higher income and higher education. Surprisingly, no significant gender difference was found in information search behavior for health care decision-making. The results also suggest that consumers with the highest tendency to use word-of-mouth are also the lowest users of the Internet in health care decision-making. Implications of these findings are discussed.

A study of Internet searches for medical information in dermatology patients: The patient-physician relationship.

PubMed

Orgaz-Molina, J; Cotugno, M; Girón-Prieto, M S; Arrabal-Polo, M A; Ruiz-Carrascosa, J C; Buendía-Eisman, A; Arias-Santiago, S

2015-01-01

The use of the Internet to search for medical information is considered by some physicians as an invasion of their medical domain and a reflection of a lack of trust in their advice and recommendations. The main objective of this study was to estimate the amount of medical information gathered from the Internet and to establish whether these online searches reflect a lower degree of patient satisfaction. A survey was conducted among 175 patients seen at the melanoma and psoriasis units of San Cecilio University Hospital in Granada, Spain between May 2010 and December 2011. Online searches for medical information were performed by 44.4% of patients who returned correctly completed questionnaires. The main reasons given for these searches were to complement appropriate information provided by the physician (67.3%) and to gather information before consultation with the physician (36.5%). Variables associated with the search for medical information on the Internet in the multivariate analysis were a higher educational level, a higher score on two items in the Need for Cognition Scale, and consultation of mass media other than the Internet. Studies with larger numbers of patients and other diseases, however, are required to confirm these results. The search for medical information is a widespread reality among patients with psoriasis and melanoma and it is not associated with a poor relationship with the physician. Dermatologists can play a beneficial role by recommending trustworthy Internet sites during the patient's visit and by promoting the development of pages by scientific societies to provide high-quality information. Copyright © 2014 Elsevier España, S.L.U. and AEDV. All rights reserved.

Accessing Suicide-Related Information on the Internet: A Retrospective Observational Study of Search Behavior

PubMed Central

2013-01-01

Background The Internet’s potential impact on suicide is of major public health interest as easy online access to pro-suicide information or specific suicide methods may increase suicide risk among vulnerable Internet users. Little is known, however, about users’ actual searching and browsing behaviors of online suicide-related information. Objective To investigate what webpages people actually clicked on after searching with suicide-related queries on a search engine and to examine what queries people used to get access to pro-suicide websites. Methods A retrospective observational study was done. We used a web search dataset released by America Online (AOL). The dataset was randomly sampled from all AOL subscribers’ web queries between March and May 2006 and generated by 657,000 service subscribers. Results We found 5526 search queries (0.026%, 5526/21,000,000) that included the keyword "suicide". The 5526 search queries included 1586 different search terms and were generated by 1625 unique subscribers (0.25%, 1625/657,000). Of these queries, 61.38% (3392/5526) were followed by users clicking on a search result. Of these 3392 queries, 1344 (39.62%) webpages were clicked on by 930 unique users but only 1314 of those webpages were accessible during the study period. Each clicked-through webpage was classified into 11 categories. The categories of the most visited webpages were: entertainment (30.13%; 396/1314), scientific information (18.31%; 240/1314), and community resources (14.53%; 191/1314). Among the 1314 accessed webpages, we could identify only two pro-suicide websites. We found that the search terms used to access these sites included “commiting suicide with a gas oven”, “hairless goat”, “pictures of murder by strangulation”, and “photo of a severe burn”. A limitation of our study is that the database may be dated and confined to mainly English webpages. Conclusions Searching or browsing suicide-related or pro-suicide webpages was

Accessing suicide-related information on the internet: a retrospective observational study of search behavior.

PubMed

Wong, Paul Wai-Ching; Fu, King-Wa; Yau, Rickey Sai-Pong; Ma, Helen Hei-Man; Law, Yik-Wa; Chang, Shu-Sen; Yip, Paul Siu-Fai

2013-01-11

The Internet's potential impact on suicide is of major public health interest as easy online access to pro-suicide information or specific suicide methods may increase suicide risk among vulnerable Internet users. Little is known, however, about users' actual searching and browsing behaviors of online suicide-related information. To investigate what webpages people actually clicked on after searching with suicide-related queries on a search engine and to examine what queries people used to get access to pro-suicide websites. A retrospective observational study was done. We used a web search dataset released by America Online (AOL). The dataset was randomly sampled from all AOL subscribers' web queries between March and May 2006 and generated by 657,000 service subscribers. We found 5526 search queries (0.026%, 5526/21,000,000) that included the keyword "suicide". The 5526 search queries included 1586 different search terms and were generated by 1625 unique subscribers (0.25%, 1625/657,000). Of these queries, 61.38% (3392/5526) were followed by users clicking on a search result. Of these 3392 queries, 1344 (39.62%) webpages were clicked on by 930 unique users but only 1314 of those webpages were accessible during the study period. Each clicked-through webpage was classified into 11 categories. The categories of the most visited webpages were: entertainment (30.13%; 396/1314), scientific information (18.31%; 240/1314), and community resources (14.53%; 191/1314). Among the 1314 accessed webpages, we could identify only two pro-suicide websites. We found that the search terms used to access these sites included "commiting suicide with a gas oven", "hairless goat", "pictures of murder by strangulation", and "photo of a severe burn". A limitation of our study is that the database may be dated and confined to mainly English webpages. Searching or browsing suicide-related or pro-suicide webpages was uncommon, although a small group of users did access websites that contain

Internet search term affects the quality and accuracy of online information about developmental hip dysplasia.

PubMed

Fabricant, Peter D; Dy, Christopher J; Patel, Ronak M; Blanco, John S; Doyle, Shevaun M

2013-06-01

The recent emphasis on shared decision-making has increased the role of the Internet as a readily accessible medical reference source for patients and families. However, the lack of professional review creates concern over the quality, accuracy, and readability of medical information available to patients on the Internet. Three Internet search engines (Google, Yahoo, and Bing) were evaluated prospectively using 3 difference search terms of varying sophistication ("congenital hip dislocation," "developmental dysplasia of the hip," and "hip dysplasia in children"). Sixty-three unique Web sites were evaluated by each of 3 surgeons (2 fellowship-trained pediatric orthopaedic attendings and 1 orthopaedic chief resident) for quality and accuracy using a set of scoring criteria based on the AAOS/POSNA patient education Web site. The readability (literacy grade level) of each Web site was assessed using the Fleisch-Kincaid score. There were significant differences noted in quality, accuracy, and readability of information depending on the search term used. The search term "developmental dysplasia of the hip" provided higher quality and accuracy compared with the search term "congenital hip dislocation." Of the 63 total Web sites, 1 (1.6%) was below the sixth grade reading level recommended by the NIH for health education materials and 8 (12.7%) Web sites were below the average American reading level (eighth grade). The quality and accuracy of information available on the Internet regarding developmental hip dysplasia significantly varied with the search term used. Patients seeking information about DDH on the Internet may not understand the materials found because nearly all of the Web sites are written at a level above that recommended for publically distributed health information. Physicians should advise their patients to search for information using the term "developmental dysplasia of the hip" or, better yet, should refer patients to Web sites that they have