Fri, 04 Jul 2008 23:50:28 BST CiteULike: Gaetan's pubmed http://www.citeulike.org/user/Gaetan/tag/pubmed CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/Gaetan/article/2948465 <i>Bioinformatics (1 July 2008), btn318.</i><br /><br />Motivation: Biomedical literature is the principal repository of biomedical knowledge, with PubMed being the most complete database collecting, organising, and analysing such textual knowledge. There are numerous efforts that attempt to exploit this information by using text mining and machine learning techniques. We developed a novel approach, called PuReD-MCL (Pubmed Related Documents-MCL), which is based on the graph clustering algorithm MCL and relevant resources from PubMed. Methods: PuReD-MCL avoids using natural language processing (NLP) techniques directly; instead, it takes advantage of existing resources, available from PubMed. PuReD-MCL then clusters documents efficiently using the MCL graph clustering algorithm, which is based on graph flow simulation. This process allows users to analyse the results by highlighting important clues, and finally to visualise the clusters and all relevant information using an interactive graph layout algorithm, for instance BioLayout Express 3D. Results: The methodology was applied to two different datasets, previously used for the validation of the document clustering tool TextQuest. The first dataset involves the organisms E. coli and yeast, whereas the second is related to Drosophila development. PuReD-MCL successfully reproduces the annotated results obtained from TextQuest, while at the same time provides additional insights into the clusters and the corresponding documents. Availability: Source code in perl and R are available from http://tartara.csd.auth.gr/~theodos/ 10.1093/bioinformatics/btn318 PuReD-MCL: a graph-based PubMed document clustering methodology T Theodosiou N Darzentas L Angelis CA Ouzounis doi:10.1093/bioinformatics/btn318 Bioinformatics (1 July 2008), btn318. 2008-07-01T14:26:39-00:00 2008 Bioinformatics btn318 clustering pubmed http://www.citeulike.org/user/Gaetan/article/2706248 <i>BMC Bioinformatics, Vol. 9 (22 April 2008), 205.</i> GAPscreener: An Automatic Tool for Screening Human Genetic Association Literature in PubMed Using the Support Vector Machine Technique Wei Yu Melinda Clyne Siobhan Dolan Ajay Yesupriya Anja Wulf Tiebin Liu Muin Khoury Marta Gwinn doi:10.1186/1471-2105-9-205 BMC Bioinformatics, Vol. 9 (22 April 2008), 205. 2008-04-23T07:16:11-00:00 2008 BMC Bioinformatics 1471-2105 9 205 pubmed http://www.citeulike.org/user/Gaetan/article/2943382 <i>Stroke; a journal of cerebral circulation (26 June 2008)</i> Searching Additional Databases Except PubMed Are Necessary for a Systematic Review. Ming-Hua Zheng Xu Zhang Qiang Ye Yong-Ping Chen doi:10.1161/STROKEAHA.107.524876 Stroke; a journal of cerebral circulation (26 June 2008) 2008-06-30T08:09:42-00:00 2008 Stroke; a journal of cerebral circulation 1524-4628 pubmed reviews systematic http://www.citeulike.org/user/Gaetan/article/2888470 <i>Genome informatics. International Conference on Genome Informatics, Vol. 18 (2007), pp. 267-276.</i><br /><br />We have developed a PubMed article recommendation system, PURE, which is based on content-based filtering. PURE has a web interface by which users can add/delete their preferred articles. Once articles are registered, PURE then performs model-based clustering of the preferred articles and recommends the highly-rated articles by the prediction using the trained model. PURE updates the PubMed articles and reports the recommendation by email on daily-base. This system will be helpful for biologists to reduce the time required for gathering information from PubMed. PURE is downloadable under GPL license, via http://www.bic.kyoto-u.ac.jp/pathway/mami/out/PURE.tar.gz. Pure: a pubmed article recommendation system based on content-based filtering. T Yoneya H Mamitsuka Genome informatics. International Conference on Genome Informatics, Vol. 18 (2007), pp. 267-276. 2008-06-12T14:20:23-00:00 2007 Genome informatics. International Conference on Genome Informatics 0919-9454 18 267 276 pubmed http://www.citeulike.org/user/Gaetan/article/2870248 <i>BMC Bioinformatics, Vol. 9, No. 1. (2008)</i><br /><br />BACKGROUND:Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed search interface, a MEDLINE citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web.RESULTS:We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics.CONCLUSIONS:The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain. PageRank without hyperlinks: reranking with PubMed related article networks for biomedical text retrieval Jimmy Lin doi:10.1186/1471-2105-9-270 BMC Bioinformatics, Vol. 9, No. 1. (2008) 2008-06-06T18:39:41-00:00 2008 BMC Bioinformatics 9 1 pubmed http://www.citeulike.org/user/Gaetan/article/2805405 <i>Nucl. Acids Res. (16 May 2008), gkn296.</i><br /><br />A particular challenge in biomedical text mining is to find ways of handling comprehensive' or associative' queries such as Find all genes associated with breast cancer'. Given that many queries in genomics, proteomics or metabolomics involve these kind of comprehensive searches we believe that a web-based tool that could support these searches would be quite useful. In response to this need, we have developed the PolySearch web server. PolySearch supports >50 different classes of queries against nearly a dozen different types of text, scientific abstract or bioinformatic databases. The typical query supported by PolySearch is Given X, find all Y's' where X or Y can be diseases, tissues, cell compartments, gene/protein names, SNPs, mutations, drugs and metabolites. PolySearch also exploits a variety of techniques in text mining and information retrieval to identify, highlight and rank informative abstracts, paragraphs or sentences. PolySearch's performance has been assessed in tasks such as gene synonym identification, protein-protein interaction identification and disease gene identification using a variety of manually assembled gold standard' text corpuses. Its f-measure on these tasks is 88, 81 and 79%, respectively. These values are between 5 and 50% better than other published tools. The server is freely available at http://wishart.biology.ualberta.ca/polysearch 10.1093/nar/gkn296 PolySearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites Dean Cheng Craig Knox Nelson Young Paul Stothard Sambasivarao Damaraju David Wishart doi:10.1093/nar/gkn296 Nucl. Acids Res. (16 May 2008), gkn296. 2008-05-16T14:44:25-00:00 2008 Nucl. Acids Res. gkn296 pubmed text_mining http://www.citeulike.org/user/Gaetan/article/2653988 <i>Bioinformatics (Oxford, England) (9 April 2008)</i><br /><br />SUMMARY: Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To address this problem, we present MedEvi, a novel search engine that imposes positional restriction on occurrences matching multi-term queries, based on the observation that terms with semantic relations which are explicitly stated in text are not found too far from each other. MedEvi further identifies additional keywords of biological and statistical significance from local context of matching occurrences in order to help users reformulate their queries for better results. AVAILABILITY: http://www.ebi.ac.uk/tc-test/textmining/medevi/ CONTACT: kim@ebi.ac.uk, pezik@ebi.ac.uk. MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline. Jung-Jae Kim Piotr Pezik Dietrich Rebholz-Schuhmann doi:10.1093/bioinformatics/btn117 Bioinformatics (Oxford, England) (9 April 2008) 2008-04-11T13:37:51-00:00 2008 Bioinformatics (Oxford, England) 1460-2059 ebm medline pubmed http://www.citeulike.org/user/Gaetan/article/2625349 <i>Journal of the Medical Library Association : JMLA, Vol. 96, No. 2. (April 2008), pp. 134-137.</i><br /><br />OBJECTIVE: The paper provides an overview of a strategy to increase utilization of online bibliographic databases by public health workers. METHODS: A web-based survey of professional staff in the Montana Department of Public Health and Human Services was conducted to assess their use of and interest in training in online bibliographic databases. Based on the findings from the assessment, the department, in collaboration with the state university, provided brief ninety-minute training sessions for interested staff on the use of PubMed. RESULTS: Seventy of 115 (61%) of staff completed the survey. Only 39% of staff reported using an online bibliographic database to conduct a literature search in the past year, and only 10% (n=7) reported having ever received any training in their use. Perceived proficiency with the use of PubMed was higher upon completion of the brief training. The majority of training participants (n=27) indicated that they were very likely to use PubMed in the next year to search the literature. CONCLUSIONS: A collaboratively designed training can increase public health workers' proficiency in and intentions of using online bibliographic databases. Increasing state public health professionals' proficiency in using PubMed. TS Harwell DG Law JL Ander SD Helgerson doi:10.3163/1536-5050.96.2.134 Journal of the Medical Library Association : JMLA, Vol. 96, No. 2. (April 2008), pp. 134-137. 2008-04-03T07:36:54-00:00 2008 Journal of the Medical Library Association : JMLA 1558-9439 96 2 134 137 pubmed training http://www.citeulike.org/user/Gaetan/article/2532283 <i>Clin Lab Sci, Vol. 21, No. 1. (2008), pp. 35-41.</i><br /><br />As the volume of biomedical literature has increased, so have the number and complexity of databases that index it. Learning to conduct an efficient literature search in an online database is an essential skill for today's clinical laboratory scientist. This article describes basic and advanced strategies for searching PubMed and the use of specialized features including MyNCBI. Searching MEDLINE via PubMed. FA Delwiche Clin Lab Sci, Vol. 21, No. 1. (2008), pp. 35-41. 2008-03-14T14:19:26-00:00 2008 Clin Lab Sci 0894-959X 21 1 35 41 medline pubmed http://www.citeulike.org/user/Gaetan/article/1896251 <i>BMC Bioinformatics, Vol. 8 (09 November 2007), 436.</i> An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology Wei Yu Ajay Yesupriya Anja Wulf Junfeng Qu Muin Khoury Marta Gwinn doi:10.1186/1471-2105-8-436 BMC Bioinformatics, Vol. 8 (09 November 2007), 436. 2007-11-10T21:48:55-00:00 2007 BMC Bioinformatics 1471-2105 8 436 pubmed http://www.citeulike.org/user/Gaetan/article/2514963 <i>Bioinformatics (6 March 2008)</i><br /><br />SUMMARY: MiSearch is an adaptive biomedical literature search tool that ranks citations based on a statistical model for the likelihood that a user will choose to view them. Citation selections are automatically acquired during browsing and used to dynamically update a likelihood model that includes authorship, journal and PubMed indexing information. The user can optionally elect to include or exclude specific features and vary the importance of timeliness in the ranking. AVAILABILITY: http://misearch.ncibi.org CONTACT: David J. States (dstates@umich.edu). MiSearch Adaptive PubMed Search Tool. David J States Alex S Ade Zachary C Wright Aaron V Bookvich Brian D Athey doi:10.1093/bioinformatics/btn033 Bioinformatics (6 March 2008) 2008-03-11T13:47:44-00:00 2008 Bioinformatics 1460-2059 pubmed http://www.citeulike.org/user/Gaetan/article/2484818 <i>Ned Tijdschr Geneeskd, Vol. 152, No. 4. (26 January 2008), pp. 221-224.</i><br /><br />For clinicians, researchers and policy makers in healthcare, it is important to keep up to date with the newest medical-scientific information. The large amount of new information makes this a difficult task. There are various techniques for keeping up to date, for instance reading systematic reviews, searching the literature at regular intervals oneself, and using the e-mail alerting services of, for example, PubMed. A new possibility is to be alerted to new scientific publications, for example, via a 'really simple syndication' (RSS)-feed. This option is now also made available by PubMed. In addition to PubMed, many other websites can now be searched systematically for new information by a RSS reader. With RSS feeds the user can be alerted to new information much faster than by an e-mail alerting service, so that one can anticipate new developments more rapidly. [Keeping up to date with the relevant literature: 'really simple syndication'-(RSS)-feeds within PubMed] E Leclercq LC Kremer Ned Tijdschr Geneeskd, Vol. 152, No. 4. (26 January 2008), pp. 221-224. 2008-03-07T15:01:11-00:00 2008 Ned Tijdschr Geneeskd 0028-2162 152 4 221 224 pubmed rss http://www.citeulike.org/user/Gaetan/article/2477596 <i>Bioinformatics (5 March 2008), btn086.</i><br /><br />Summary: Using literature databases one can find not only known and true relations between processes but also less studied, non-obvious associations. The main problem with discovering such type of relevant biological information is "selection". The ability to distinguish between a true correlation (e.g. between different types of biological processes) and random chance that this correlation is statistically significant is crucial for any bio-medical research, literature mining being no exception. This problem is especially visible when searching for information which hasn't been studied and described in many publications. Therefore a novel bio-linguistic statistical method is required, capable of "selecting" true correlations, even when they are low-frequency associations. In this paper we present such statistical approach based on Z-score and implemented in a web-based application "e-LiSe". Availability: The software is available at http://miron.ibb.waw.pl/elise/ Supplementary materials are available at http://miron.ibb.waw.pl/elise.supplementary/ Contact: piotr@ibb.waw.pl 10.1093/bioinformatics/btn086 e-LiSe - an online tool for finding needles in the "(Medline) haystack" Arek Gladki Pawel Siedlecki Szymon Kaczanowski Piotr Zielenkiewicz doi:10.1093/bioinformatics/btn086 Bioinformatics (5 March 2008), btn086. 2008-03-06T07:47:04-00:00 2008 Bioinformatics btn086 pubmed http://www.citeulike.org/user/Gaetan/article/2459839 <i>Conf Proc IEEE Eng Med Biol Soc, Vol. 1 (2006), pp. 5779-5782.</i><br /><br />The numbers of articles and journals that are published are increasing at a considerable rate, and the published information is growing continuously and fast. Because of this, researches to acquire knowledge automatically have been carried out in the areas of information retrieval, information extraction and text mining. Information retrieval approaches are good for specific topics that the number of related articles is small. But, if the number is bigger, searching skill and knowledge acquisition ability are useless. Though many efforts have been made to extract information from literature, many approaches have concentrated on specific entities, such as proteins, genes and their interactions, and much information is still remained in unstructured text. So, we have developed a system that discovers relations between various categories of biomedical entities. Our system collects abstracts from PubMed by queries representing a topic and visualizes relationship from the collection by automatic information extraction. BioProber: software system for biomedical relation discovery from PubMed. H Jang J Lim JH Lim SJ Park KC Lee doi:10.1109/IEMBS.2006.259838 Conf Proc IEEE Eng Med Biol Soc, Vol. 1 (2006), pp. 5779-5782. 2008-03-03T08:09:59-00:00 2006 Conf Proc IEEE Eng Med Biol Soc 1557-170X 1 5779 5782 pubmed http://www.citeulike.org/user/Gaetan/article/2389647 <i>Journal of Biomedical Discovery and Collaboration, Vol. 3 (15 February 2008), 2.</i> Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search results Neil Smalheiser Wei Zhou Vetle Torvik doi:10.1186/1747-5333-3-2 Journal of Biomedical Discovery and Collaboration, Vol. 3 (15 February 2008), 2. 2008-02-17T01:30:16-00:00 2008 Journal of Biomedical Discovery and Collaboration 1747-5333 3 2 pubmed http://www.citeulike.org/user/Gaetan/article/2366377 <i>Intern Emerg Med (9 February 2008)</i> Advice for health-care professionals on how to retrieve more efficiently scientifically strong and up-to-date studies on treatments by PubMed. Salvatore Corrao Rosario Scaglione Daniela Colomba Luigi Calvo Giuseppe Licata doi:10.1007/s11739-008-0115-5 Intern Emerg Med (9 February 2008) 2008-02-12T15:32:37-00:00 2008 Intern Emerg Med 1828-0447 pubmed http://www.citeulike.org/user/Gaetan/article/1845865 <i>BMC Bioinformatics, Vol. 8, No. 1. (2007)</i><br /><br />BACKGROUND:We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance---but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH in MEDLINE.RESULTS:The pmra retrieval model was compared against bm25, a competitive probabilistic model that shares theoretical similarities. Experiments using the test collection from the TREC 2005 genomics track shows a small but statistically significant improvement of pmra over bm25 in terms of precision.CONCLUSIONS:Our experiments suggest that the pmra model provides an effective ranking algorithm for related article search. PubMed related articles: a probabilistic topic-based model for content similarity Jimmy Lin John Wilbur doi:10.1186/1471-2105-8-423 BMC Bioinformatics, Vol. 8, No. 1. (2007) 2007-10-31T08:44:23-00:00 2007 BMC Bioinformatics 8 1 pubmed http://www.citeulike.org/user/Gaetan/article/2141103 <i>Eura Medicophys, Vol. 43, No. 4. (December 2007), pp. 563-569.</i><br /><br />This article presents several popular free-access biomedical databases (general, genetic, pharmacological, evidence-based oriented, or dealing with health technology assessment) from which researchers can select the best tool for the purpose and context of a specific research. Some gateways for searching across multiple databases that provide a ”one-stop shopping” point of access are also presented. Beyond PubMed. Other free-access biomedical databases. E Giglia Eura Medicophys, Vol. 43, No. 4. (December 2007), pp. 563-569. 2007-12-18T14:18:02-00:00 2007 Eura Medicophys 0014-2573 43 4 563 569 biomedical_databases pubmed http://www.citeulike.org/user/Gaetan/article/2089683 <i>Rev Chir Orthop Reparatrice Appar Mot, Vol. 93, No. 6. (October 2007), pp. 619-626.</i><br /><br />La littérature scientifique a pris une place croissante dans notre pratique quotidienne. L'abondance de cette littérature a rendu incontournable l'utilisation d'outils tels que les bases de données pour obtenir des résultats de recherche pertinents. Force est de constater que nous sommes peu préparés à l'utilisation de tels outils... Medline est la base de donnée la plus répandue et nous proposons de détailler son fonctionnement. Après une brève définition, nous détaillons son mode d'organisation et de mise à jour. Nous expliquons comment élaborer une recherche efficace notamment par l'emploi des mots-clés et des opérateurs booléens. Un choix précis conditionne la pertinence du résultat de la recherche. À cet effet, nous détaillons l'utilisation du répertoire MESH pour choisir un mot-clé ainsi que ses diverses options accessoires. Les fonctions annexes et services associés de la base de données Medline sont également passés en revue. Enfin la gestion des résultats, leur affichage et leur exploitation sont détaillés. Bibliographie sur Medline-PubMed. Chercher l'information pertinente ou comment bien utiliser une base de données D Ollat X Bajard C Pero G Versier Rev Chir Orthop Reparatrice Appar Mot, Vol. 93, No. 6. (October 2007), pp. 619-626. 2007-12-11T14:26:59-00:00 2007 Rev Chir Orthop Reparatrice Appar Mot 0035-1040 93 6 619 626 medline pubmed http://www.citeulike.org/user/Gaetan/article/2048221 <i>Allergol Immunopathol (Madr), Vol. 35, No. 6. (November 2007), pp. 264-275.</i><br /><br />INTRODUCTION: PubMed is the most important of the non-specialized databases on biomedical literature. International and quickly updated is elaborated by the American Government and contains only information about papers published in scientific journal/s. Although it can be used as an unique Data Base, as a matter of fact is the addition of several subgroups (among them MEDLINE) that can be searched simultaneously. OBJECTIVES: To present the main characteristics of PubMed, as well as the most important procedures of search, for obtaining efficient results in searches on allergology. CHARACTERISTICS AND SEARCH PROCEDURES: PubMed is elaborated by the American Administration, that condition the character of the registered papers, 90 % of them are written in English in American (50 %) or British (20 %) Journals. Because of this, the information for certain specialties or countries must be obtained from other sources. This paper shows how PubMed allows to search in natural language due to the Automatic Term Mapping that links terms from the natural language with the descriptors producing searches with a higher sensitivity although with a low specificity. Nevertheless the MeSH (Medical Subject Headings) thesaurus allows to translate those terms from the natural language to the equivalent descriptor, as well as to make queries in the PubMed's documental language with a high specificity but with lower sensitivity than the natural language. The use of union (OR), intersection (AND) and exclusion (NOT) operators, as well as tags, such as delimiters of the search fields, allows to increase the specificity of the results. Similar results may be obtained with the use of Limits. Searches done using Clinical Queries are very interesting due to their direct clinical application and because allow to find systematic reviews, metaanalysis or clinically oriented papers (treatment, diagnostic, etiology, prognosis or clinical prediction guides) on the area of interest. Other procedures such as the Index, History of searches, and the widening of the selection using Related Articles and the storing of separate results in the Clipboard to be kept by the user, are presented in this paper. Efficient bibliographic searches on Allergology using PubMed. J M Sáez Gómez E Aguinaga Ontoso J M Negro Álvarez F Guillén-Grima J C Ivancevich C M Bozzola Allergol Immunopathol (Madr), Vol. 35, No. 6. (November 2007), pp. 264-275. 2007-12-03T08:13:18-00:00 2007 Allergol Immunopathol (Madr) 0301-0546 35 6 264 275 pubmed http://www.citeulike.org/user/Gaetan/article/1938004 <i>(November 2006)</i> Current Status of Open Access in Biomedical Field-the Comparison of Countries Related to the Impact of National Policies Mamiko Matsubayashi Keiko Kurata Yukiko Sakai Tomoko Morioka Shinya Kato Shinji Mine Shuichi Ueda (November 2006) 2007-11-19T12:23:56-00:00 2006 communication open_acess pubmed scholarly http://www.citeulike.org/user/Gaetan/article/1866895 <i>J Med Libr Assoc, Vol. 95, No. 4. (October 2007), pp. 442-445.</i> Comparing test searches in PubMed and Google Scholar. M Shultz doi:10.3163/1536-5050.95.4.442 J Med Libr Assoc, Vol. 95, No. 4. (October 2007), pp. 442-445. 2007-11-05T08:46:07-00:00 2007 J Med Libr Assoc 1558-9439 95 4 442 445 pubmed http://www.citeulike.org/user/Gaetan/article/1745680 <i>Eura Medicophys, Vol. 43, No. 3. (September 2007), pp. 427-437.</i> PubMed at its best. Useful skills to perform an effective search, save it and automatically receive updates. E Giglia Eura Medicophys, Vol. 43, No. 3. (September 2007), pp. 427-437. 2007-10-09T13:42:59-00:00 2007 Eura Medicophys 0014-2573 43 3 427 437 pubmed http://www.citeulike.org/user/Gaetan/article/1723554 <i>Med Trop (Mars), Vol. 67, No. 3. (June 2007), pp. 303-308.</i><br /><br />The PubMed search engine is an essential tool to stay abreast of the latest medical literature on specific topics. While the basic search techniques are common knowledge, the ability to use medical subject headings properly is an essential in obtaining valuable references. The purpose of this article is to explain what medical subject headings are and how they can be used to improve the results of reference searches in PubMed. [Using PubMed subject headings to enhance reference searches] N Lefebvre J Margery A N'Diaye D Farhi K Ba-Fall A Niang SB Gning JM Debonne Med Trop (Mars), Vol. 67, No. 3. (June 2007), pp. 303-308. 2007-10-03T10:20:42-00:00 2007 Med Trop (Mars) 0025-682X 67 3 303 308 mesh pubmed http://www.citeulike.org/user/Gaetan/article/1688552 <i>Journal of the American Society for Information Science and Technology, Vol. 9999, No. 9999. (2007), NA.</i><br /><br />The study adopts a naturalistic approach to investigate users' interaction with a browsable MeSH (medical subject headings) display designed to facilitate query construction for the PubMed bibliographic database. The purpose of the study is twofold: first, to test the usefulness of a browsable interface utilizing the principle of faceted classification; and second, to investigate users' preferred query submission methods in different problematic situations.An interface that incorporated multiple query submission methods - the conventional single-line query box as well as methods associated the faceted classification display was constructed. Participants' interactions with the interface were monitored remotely over a period of 10 weeks; information about their problematic situations and information retrieval behaviors were also collected during this time. The traditional controlled experiment was not adequate in answering the author's research questions; hence, the author provides his rationale for a naturalistic approach.The study's findings show that there is indeed a selective compatibility between query submission methods provided by the MeSH display and users' problematic situations. The query submission methods associated with the display were found to be the preferred search tools when users' information needs were vague and the search topics unfamiliar.The findings support the theoretical proposition that users engaging in an information retrieval process with a variety of problematic situations need different approaches. The author argues that rather than treat the information retrieval system as a general purpose tool, more attention should be given to the interaction between the functionality of the tool and the characteristics of users' problematic situations. Browsing and searching in a faceted information space: A naturalistic study of PubMed users' interaction with a display tool Muh-Chyun Tang doi:10.1002/asi.20689 Journal of the American Society for Information Science and Technology, Vol. 9999, No. 9999. (2007), NA. 2007-09-24T06:40:27-00:00 2007 Journal of the American Society for Information Science and Technology 9999 9999 NA mesh pubmed http://www.citeulike.org/user/Gaetan/article/1688531 <i>FASEB J (20 September 2007)</i><br /><br />The evolution of the electronic age has led to the development of numerous medical databases on the World Wide Web, offering search facilities on a particular subject and the ability to perform citation analysis. We compared the content coverage and practical utility of PubMed, Scopus, Web of Science, and Google Scholar. The official Web pages of the databases were used to extract information on the range of journals covered, search facilities and restrictions, and update frequency. We used the example of a keyword search to evaluate the usefulness of these databases in biomedical information retrieval and a specific published article to evaluate their utility in performing citation analysis. All databases were practical in use and offered numerous search facilities. PubMed and Google Scholar are accessed for free. The keyword search with PubMed offers optimal update frequency and includes online early articles; other databases can rate articles by number of citations, as an index of importance. For citation analysis, Scopus offers about 20% more coverage than Web of Science, whereas Google Scholar offers results of inconsistent accuracy. PubMed remains an optimal tool in biomedical electronic research. Scopus covers a wider journal range, of help both in keyword searching and citation analysis, but it is currently limited to recent articles (published after 1995) compared with Web of Science. Google Scholar, as for the Web in general, can help in the retrieval of even the most obscure information but its use is marred by inadequate, less often updated, citation information.-Falagas, M. E., Pitsouni, E I., Malietzis, G. A., and Pappas, G. Comparison of Pub Med, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. Matthew E Falagas Eleni I Pitsouni George A Malietzis Georgios Pappas doi:10.1096/fj.07-9492LSF FASEB J (20 September 2007) 2007-09-24T06:31:23-00:00 2007 FASEB J 1530-6860 pubmed http://www.citeulike.org/user/Gaetan/article/987747 <i>AMIA Annu Symp Proc (2005)</i><br /><br />PubMed Informer is a Web-based monitoring tool for topics of interest from MEDLINE/PubMed primarily designed for healthcare professionals. Five tracking methods are available: Web access, e-mail, Short Message Service (SMS), PDA downloads and RSS feeds. PubMed Informer delivers focused search updates and specific information to users with varying information-seeking practices. PubMed Informer: monitoring MEDLINE/PubMed through e-mail alerts, SMS, PDA downloads and RSS feeds. M Muin P Fontelo M Ackerman AMIA Annu Symp Proc (2005) 2006-12-10T12:07:53-00:00 2005 AMIA Annu Symp Proc 1559-4076 pubmed rss http://www.citeulike.org/user/Gaetan/article/1356997 <i>(2007), pp. 1203-1204.</i> Tag clouds for summarizing web search results Byron Kuo Thomas Hentrich Benjamin Mark Wilkinson doi:10.1145/1242572.1242766 (2007), pp. 1203-1204. 2007-06-02T11:13:57-00:00 2007 1203 1204 ACM Press pubmed http://www.citeulike.org/user/Gaetan/article/882265 <i>BMC Bioinformatics, Vol. 7 (02 October 2006), 424.</i> PubFocus: Semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm Maksim Plikus Zina Zhang Cheng-Ming Chuong doi:10.1186/1471-2105-7-424 BMC Bioinformatics, Vol. 7 (02 October 2006), 424. 2006-10-03T03:18:50-00:00 2006 BMC Bioinformatics 1471-2105 7 424 medline pubmed http://www.citeulike.org/user/Gaetan/article/1394690 <i>BMC Medical Informatics and Decision Making, Vol. 7 (15 June 2007), 16.</i> Utilization of the PICO framework to improve searching PubMed for clinical questions Connie Schardt Martha Adams Thomas Owens Sheri Keitz Paul Fontelo doi:10.1186/1472-6947-7-16 BMC Medical Informatics and Decision Making, Vol. 7 (15 June 2007), 16. 2007-06-16T21:53:16-00:00 2007 BMC Medical Informatics and Decision Making 1472-6947 7 16 pubmed http://www.citeulike.org/user/Gaetan/article/1582875 <i>Comput Biol Med, Vol. 37, No. 9. (September 2007), pp. 1252-1258.</i><br /><br />PubMed and HighWire Press are both useful medical literature search engines available for free to anyone on the internet. We measured retrieval accuracy, number of results generated, retrieval speed, features and search tools on HighWire Press and PubMed using the quick search features of each. We found that using HighWire Press resulted in a higher likelihood of retrieving the desired article and higher number of search results than the same search on PubMed. PubMed was faster than HighWire Press in delivering search results regardless of search settings. There are considerable differences in search features between these two search engines. PubMed vs. HighWire Press: A head-to-head comparison of two medical literature search engines. TE Vanhecke MA Barnes J Zimmerman S Shoichet doi:10.1016/j.compbiomed.2006.11.012 Comput Biol Med, Vol. 37, No. 9. (September 2007), pp. 1252-1258. 2007-08-22T13:37:52-00:00 2007 Comput Biol Med 0010-4825 37 9 1252 1258 pubmed http://www.citeulike.org/user/Gaetan/article/1640618 <i>Nephrologie & Therapeutique, Vol. In Press, Corrected Proof</i> Recherche bibliographique medicale avec Medline-Pubmed. Une approche pratique basee sur l'exemple Philippe Eveillard Thierry Hannedouche doi:10.1016/j.nephro.2007.06.016 Nephrologie & Therapeutique, Vol. In Press, Corrected Proof 2007-09-10T08:31:13-00:00 Nephrologie & Therapeutique In Press, Corrected Proof pubmed