CiteULike: Gaetan's medline

["Méta-analyse": a web-based tool for research and analysis of radiology papers.]

N Garcelon — 2008-07-22T13:25:16-00:00

Journal de radiologie, Vol. 89, No. 6. (June 2008), pp. 817-820.

Finding articles providing answers to specific clinical questions is greatly facilitated by the availability of indexed Medline abstracts using the Pubmed search engine. Nonetheless, the large number of references sometimes requires a time-consuming review of multiple abstracts. In order to streamline the search process, we have created a tool facilitating the search and review of these abstracts. We present here this tool named "Méta-analyse".

An update on Uniform Resource Locator (URL) decay in MEDLINE abstracts and measures for its mitigation.

Erick Ducut — 2008-06-12T08:03:34-00:00

BMC Medical Informatics and Decision Making, Vol. 8 (11 June 2008), 23.

Anni 2.0: a multipurpose text-mining tool for the life sciences

Rob Jelier — 2008-06-13T04:46:41-00:00

Genome Biology, Vol. 9, No. 6. (2008)

Anni 2.0 is an online tool (http://biosemantics.org/anni/) to aid the biomedical researcher with a broad range of information needs. Anni provides an ontology-based interface to Medline and retrieves documents and associations for several classes of biomedical concepts, including genes, drugs and diseases, with established text-mining technology. In this article we illustrate Anni's usability by applying the tool to two use cases: interpretation of a set differentially expressed genes, and literature-based knowledge discovery.

Developing a Sensitive Search Strategy in MEDLINE to Retrieve Studies on Assessment of the Diagnostic Performance of Imaging Techniques

Margaret Astin — 2008-04-25T07:32:38-00:00

Radiology, Vol. 247, No. 2. (1 May 2008), pp. 365-373.

Purpose: To prospectively develop a search strategy in MEDLINE for identifying studies on the diagnostic performance of any imaging modality, with maximized and minimized retrieval of relevant and irrelevant studies, respectively. Materials and Methods: Predefined inclusion criteria were used to conduct a hand search of two sets of radiologic journal articles for studies on assessment of the diagnostic performance of imaging techniques. These two sets of articles formed independent derivation and validation record sets for developing and evaluating the search strategy. The sensitivity and positive predictive values (PPVs) of search terms from the derivation reference-standard set of records were used to select terms and develop two components of the search strategy. The first component was used to identify any study (from the imaging literature) in which diagnostic test performance was assessed. The second component was used to identify studies of any imaging modality. The two components were combined in the final search strategy. The sensitivity, specificity, and PPV of the search strategy in the derivation and validation record sets were calculated. Results: The final search strategy had a sensitivity of 92.8%, a specificity of 58.5%, and a PPV of 25.1% for retrieval of the derivation set of records. Validation with an independent set of records gave a sensitivity of 91.9% (95% confidence interval [CI]: 87.1%, 95.1%), a specificity of 52.2% (95% CI: 49.2%, 55.2%), and a PPV of 25.1% (95% CI: 22.0%, 28.5%). Removal of irrelevant publication types further improved specificity and PPV in the validation set: to 77.6% (95% CI: 75.0%, 80.0%) and 40.9% (95% CI: 36.2%, 45.7%), respectively. The volume of imaging literature retrieved from MEDLINE by using the described search strategy has tripled since 1975. Conclusion: A sensitive search strategy to identify studies of the diagnostic performance of any imaging test was developed and validated. The retrieval estimates of this strategy in MEDLINE are adequate to develop a register of studies. Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/2472070101/DC1 http://radiology.rsnajnls.org/cgi/content/full/2472070101/DC2 (C) RSNA, 2008 10.1148/radiol.2472070101

URL decay in MEDLINE - a 4-year follow-up study

Jonathan Wren — 2008-04-16T08:15:26-00:00

Bioinformatics (15 April 2008), btn127.

Motivation: Internet-based electronic resources, as given by Uniform Resource Locators (URLs), are being increasingly used in scientific publications but are also becoming inaccessible in a time-dependant manner, a phenomenon documented across disciplines. Initial reports brought attention to the problem, spawning methods of effectively preserving URL content while some journals adopted policies regarding URL publication and begun storing supplementary information on journal websites. Thus, a re-examination of URL growth and decay in the literature is merited to see if the problem has grown or been mitigated by any of these changes Results: After the 2003 study, three follow-up studies were conducted in 2004, 2005 and 2007. Unfortunately, no significant change was found in the rate of URL decay among any of the studies. However, only 5% of URLs cited more than twice have decayed versus 20% of URLs cited once or twice. The most common types of lost content were computer programs (43%), followed by scholarly content (38%) and databases (19%). Compared to URLs still available, no lost content type was significantly over or under-represented. Searching for 30 of these websites using Google, 11 (37%) were found relocated to different URLs. Conclusions: URL decay continues unabated, but URLs published by organizations tend to be more stable. Repeated citation of URLs suggests calculation of an electronic impact factor (eIF) would be an objective, quantitative way to measure the impact of Internet-based resources on scientific research. Contact: Jonathan-Wren@OMRF.org 10.1093/bioinformatics/btn127

MedEvi: Retrieving textual evidence of relations between biomedical concepts from Medline.

Jung-Jae Kim — 2008-04-11T13:37:51-00:00

Bioinformatics (Oxford, England) (9 April 2008)

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.

Searching MEDLINE via PubMed.

FA Delwiche — 2008-03-14T14:19:26-00:00

Clin Lab Sci, Vol. 21, No. 1. (2008), pp. 35-41.

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.

MScanner: a classifier for retrieving Medline citations

Graham Poulter — 2008-02-19T19:04:13-00:00

BMC Bioinformatics, Vol. 9, No. 1. (2008)

BACKGROUND:Keyword searching through PubMed and other systems is the standard means of retrieving information from Medline. However, ad-hoc retrieval systems do not meet all of the needs of databases that curate information from literature, or of text miners developing a corpus on a topic that has many terms indicative of relevance. Several databases have developed supervised learning methods that operate on a filtered subset of Medline, to classify Medline records so that fewer articles have to be manually reviewed for relevance. A few studies have considered generalisation of Medline classification to operate on the entire Medline database in a non-domain-specific manner, but existing applications lack speed, available implementations, or a means to measure performance in new domains.RESULTS:MScanner is an implementation of a Bayesian classifier that provides a simple web interface for submitting a corpus of relevant training examples in the form of PubMed IDs and returning results ranked by decreasing probability of relevance. For maximum speed it uses the Medical Subject Headings (MeSH) and journal of publication as a concise document representation, and takes roughly 90 seconds to return results against the 16 million records in Medline. The web interface provides interactive exploration of the results, and cross validated performance evaluation on the relevant input against a random subset of Medline. We describe the classifier implementation, cross validate it on three domain-specific topics, and compare its performance to that of an expert PubMed query for a complex topic. In cross validation on the three sample topics against 100,000 random articles, the classifier achieved excellent separation of relevant and irrelevant article score distributions, ROC areas between 0.97 and 0.99, and averaged precision between 0.69 and 0.92.CONCLUSIONS:MScanner is an effective non-domain-specific classifier that operates on the entire Medline database, and is suited to retrieving topics for which many features may indicate relevance. Its web interface simplifies the task of classifying Medline citations, compared to building a pre-filter and classifier specific to the topic. The data sets and open source code used to obtain the results in this paper are available on-line and as supplementary material, and the web interface may be accessed at http://mscanner.stanford.edu.

Usefulness of Systematic Review Search Strategies in Finding Child Health Systematic Reviews in MEDLINE

Nicole Boluyt — 2008-02-05T15:48:47-00:00

Arch Pediatr Adolesc Med, Vol. 162, No. 2. (2008), pp. 111-116.

Objective To determine the sensitivity and precision of existing search strategies for retrieving child health systematic reviews in MEDLINE using PubMed. Design Filter (diagnostic) accuracy study. We identified existing search strategies for systematic reviews, combined them with a filter that identifies articles relevant to child health, and applied the combination in MEDLINE to a reference set of child health systematic reviews. Main Outcome Measures Total number of records retrieved, sensitivity, and precision. Results We tested 9 search filters. Sensitivity of the systematic review filters combined with the child filter ranged from 68% to 96%; sensitivity of the child filter alone was 98%. The number of records retrieved with PubMed (limited to January 1990-January 2006) by the systematic review filters combined with the child filter ranged from 7861 to 618 053. Precision for the combined filters ranged from 2% to 52%. Because of poor reporting of specific systematic review criteria in both titles and abstracts, in 25% of the records screened we were unsure whether the article concerned a systematic review according to our definition. Conclusions The high numbers of records yielded by sensitive search strategies and the low precision threaten the use of systematic reviews for clinical decision making and guideline development. Reporting of specific systematic review criteria in titles and abstracts is poor, and reporting recommendations given by Quality of Reporting of Meta-analyses (QUOROM) should be used more strictly. To make identification using MEDLINE easier, there is an urgent need to set minimal criteria that any review should fulfill for it to be indexed as a systematic review.

Real-time EBM: from bed board to keyboard and back.

R Stark — 2008-01-14T09:10:00-00:00

J Gen Intern Med, Vol. 22, No. 12. (December 2007), pp. 1656-1660.

BACKGROUND: To practice Evidence-Based Medicine (EBM), physicians must quickly retrieve evidence to inform medical decisions. Internal Medicine (IM) residents receive little formal education in electronic database searching, and have identified poor searching skills as a barrier to practicing EBM. OBJECTIVE: To design and implement a database searching tutorial for IM residents on inpatient rotations and to evaluate its impact on residents' skill and comfort searching MEDLINE and filtered EBM resources. DESIGN: Randomized controlled trial. Residents randomized to the searching tutorial met for up to 6 1-hour small group sessions to search for answers to questions about current hospitalized patients. PARTICIPANTS: Second- and 3rd-year IM residents. MEASUREMENTS: Residents in both groups completed an Objective Structured Searching Evaluation (OSSE), searching for primary evidence to answer 5 clinical questions. OSSE outcomes were the number of successful searches, search times, and techniques utilized. Participants also completed self-assessment surveys measuring frequency and comfort using EBM databases. RESULTS: During the OSSE, residents who participated in the intervention utilized more searching techniques overall (p < .01) and used PubMed's Clinical Queries more often (p < .001) than control residents. Searching "success" and time per completed search did not differ between groups. Compared with controls, intervention residents reported greater comfort using MEDLINE (p < .05) and the Cochrane Library (p < .05) on post-intervention surveys. The groups did not differ in comfort using ACP Journal Club, or in self-reported frequency of use of any databases. CONCLUSIONS: An inpatient EBM searching tutorial improved searching techniques of IM residents and resulted in increased comfort with MEDLINE and the Cochrane Library, but did not impact overall searching success.

Ontology-Based MEDLINE Document Classification

Fabrice Camous — 2008-01-10T20:14:29-00:00

Vol. 4414 (2007), pp. 439-452.

Using MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles.

Hong Yu — 2006-08-29T20:45:49-00:00

J Biomed Inform (7 June 2006)

Biomedical abbreviations and acronyms are widely used in biomedical literature. Since many of them represent important content in biomedical literature, information retrieval and extraction benefits from identifying the meanings of those terms. On the other hand, many abbreviations and acronyms are ambiguous, it would be important to map them to their full forms, which ultimately represent the meanings of the abbreviations. In this study, we present a semi-supervised method that applies MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles. We first automatically generated from the MEDLINE abstracts a dictionary of abbreviation-full pairs based on a rule-based system that maps abbreviations to full forms when full forms are defined in the abstracts. We then trained on the MEDLINE abstracts and predicted the full forms of abbreviations in full-text journal articles by applying supervised machine-learning algorithms in a semi-supervised fashion. We report up to 92% prediction precision and up to 91% coverage.

Extracting semantic predications from Medline citations for pharmacogenomics.

CB Ahlers — 2007-12-21T14:22:10-00:00

Pac Symp Biocomput (2007), pp. 209-220.

We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.

An active visual search interface for Medline.

W Xuan — 2007-12-17T08:09:57-00:00

Comput Syst Bioinformatics Conf, Vol. 6 (2007), pp. 359-369.

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.

Bibliographie sur Medline-PubMed. Chercher l'information pertinente ou comment bien utiliser une base de données

D Ollat — 2007-12-11T14:26:59-00:00

Rev Chir Orthop Reparatrice Appar Mot, Vol. 93, No. 6. (October 2007), pp. 619-626.

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.

The development of the Medical Literature Analysis and Retrieval System (MEDLARS).

CR Dee — 2007-12-07T07:46:02-00:00

J Med Libr Assoc, Vol. 95, No. 4. (October 2007), pp. 416-425.

OBJECTIVE: The research provides a chronology of the US National Library of Medicine's (NLM's) contribution to access to the world's biomedical literature through its computerization of biomedical indexes, particularly the Medical Literature Analysis and Retrieval System (MEDLARS). METHOD: Using material gathered from NLM's archives and from personal interviews with people associated with developing MEDLARS and its associated systems, the author discusses key events in the history of MEDLARS. DISCUSSION: From the development of the early mechanized bibliographic retrieval systems of the 1940s and to the beginnings of online, interactive computerized bibliographic search systems of the early 1970s chronicled here, NLM's contributions to automation and bibliographic retrieval have been extensive. CONCLUSION: As NLM's technological experience and expertise grew, innovative bibliographic storage and retrieval systems emerged. NLM's accomplishments regarding MEDLARS were cutting edge, placing the library at the forefront of incorporating mechanization and technologies into medical information systems.

Using discourse analysis to improve text categorization in MEDLINE.

P Ruch — 2007-11-29T19:56:28-00:00

Medinfo, Vol. 12, No. Pt 1. (2007), pp. 710-715.

PROBLEM: Automatic keyword assignment has been largely studied in medical informatics in the context of the MEDLINE database, both for helping search in MEDLINE and in order to provide an indicative "gist" of the content of an article. Automatic assignment of Medical Subject Headings (MeSH), which is formally an automatic text categorization task, has been proposed using different methods or combination of methods, including machine learning (naïve Bayes, neural networks..), linguistically-motivated methods (syntactic parsing, semantic tagging, or information retrieval. METHODS: In the present study, we propose to evaluate the impact of the argumentative structures of scientific articles to improve the categorization effectiveness of a categorizer, which combines linguistically-motivated and information retrieval methods. Our argumentative categorizer, which uses representation levels inherited from the field of discourse analysis, is able to classify sentences of an abstract in four classes: PURPOSE; METHODS; RESULTS and CONCLUSION. For the evaluation, the OHSUMED collection, a sample of MEDLINE, is used as a benchmark. For each abstract in the collection, the result of the argumentative classifier, i.e. the labeling of each sentence with an argumentative class, is used to modify the original ranking of the MeSH categorizer. RESULTS: The most effective combination (+2%, p<0.003) strongly overweights the METHODS section and moderately the RESULTS and CONCLUSION section. CONCLUSION: Although modest, the improvement brought by argumentative features for text categorization confirms that discourse analysis methods could benefit text mining in scientific digital libraries.

Deja vu A Study of Duplicate Citations in Medline

Mounir Errami — 2007-12-03T07:40:20-00:00

Bioinformatics (1 December 2007), btm574.

Motivation: Duplicate publication impacts the quality of the scientific corpus, has been difficult to detect, and studies this far have been limited in scope and size .Using text similarity searches, we were able to identify signatures of duplicate citations among a body of abstracts. Results: A sample of 62,213 Medline citations was examined and a database of manually verified duplicate citations was created to study author publication behavior. We found that 0.04% of the citations with no shared authors were highly similar and are thus potential cases of plagiarism. 1.35% with shared authors were sufficiently similar to be considered a duplicate. Extrapolating, this would correspond to 3,500 and 117,500 duplicate citations in total, respectively. Availability: eTBLAST, an automated citation matching tool, and Deja vu, the duplicate citation database, are freely available at http://invention.swmed.edu/ and http:/spore.swmed.edu/dejavu. Contact: Harold.Garner@utsouthwestern.edu 10.1093/bioinformatics/btm574

Text processing through Web services: Calling Whatizit

Dietrich Rebholz-Schuhmann — 2007-11-15T15:47:04-00:00

Bioinformatics (15 November 2007), btm557.

Motivation: Text-mining (TM) solutions could turn are developing into efficient services to researchers in the biomedical research community. Such solutions have to scale with the growing number and size of resources (e.g., available controlled vocabularies), with the amount of literature to be processed (e.g., about 17 million documents in PubMed) and with the demands of the user community (e.g., different methods for fact extraction). These demands induce the development of server-based solutions that can be accessed programmatically. Whatizit is a suite of modules that analyse text for contained information, e.g. any own text documents, scientific publications or Medline abstracts. Each module identifies terms and then links them to the corresponding entries in bioinformatics databases such as UniProtKb/Swiss-Prot data entries and gene ontology concepts. Other modules identify a set of selected annotation types like the set produced by the EBIMed analysis pipeline for proteins. In the case of Medline abstracts, Whatizit offers access to EBI's inhouse installation via PMID or term query. For large quantities of own text, the server can be operated in a streaming mode. (http://www.ebi.ac.uk/webservices/whatizit) 10.1093/bioinformatics/btm557

Knowledge-based Methods to Help Clinicians Find Answers in MEDLINE

Charles Sneiderman — 2007-11-08T08:21:38-00:00

J Am Med Inform Assoc, Vol. 14, No. 6. (1 November 2007), pp. 772-780.

ObjectivesLarge databases of published medical research can support clinical decision making by providing physicians with the best available evidence. The time required to obtain optimal results from these databases using traditional systems often makes accessing the databases impractical for clinicians. This article explores whether a hybrid approach of augmenting traditional information retrieval with knowledge-based methods facilitates finding practical clinical advice in the research literature. DesignThree experimental systems were evaluated for their ability to find MEDLINE citations providing answers to clinical questions of different complexity. The systems (SemRep, Essie, and CQA-1.0), which rely on domain knowledge and semantic processing to varying extents, were evaluated separately and in combination. Fifteen therapy and prevention questions in three categories (general, intermediate, and specific questions) were searched. The first 10 citations retrieved by each system were randomized, anonymized, and evaluated on a three-point scale. The reasons for ratings were documented. MeasurementsMetrics evaluating the overall performance of a system (mean average precision, binary preference) and metrics evaluating the number of relevant documents in the first several presented to a physician were used. ResultsScores (mean average precision = 0.57, binary preference = 0.71) for fusion of the retrieval results of the three systems are significantly (p < 0.01) better than those for any individual system. All three systems present three to four relevant citations in the first five for any question type. ConclusionThe improvements in finding relevant MEDLINE citations due to knowledge-based processing show promise in assisting physicians to answer questions in clinical practice. 10.1197/jamia.M2407

À la recherche des données validées (4)- Les filtres « validants » de Medline

P Eveillard — 2007-10-16T09:00:27-00:00

La revue du praticien Médecine générale (16 October 2007)

Relemed: Sentence-level search engine with relevance score for the MEDLINE database of biomedical articles

Mir Siadaty — 2007-01-12T00:42:51-00:00

BMC Medical Informatics and Decision Making, Vol. 7 (10 January 2007), 1.

PICO Linguist and BabelMeSH: Development and Partial Evaluation of Evidence-based Multilanguage Search Tools for MEDLINE/PubMed.

P Fontelo — 2007-10-04T15:14:52-00:00

Stud Health Technol Inform, Vol. 129 (2007), pp. 817-821.

PICO Linguist and BabelMeSH are multilanguage search tools intended for users whose native language is not English. A database of medical terms was created using concept identification equivalents of English terms to other languages. The primary sources of vocabularies were UMLS, MeSH, WHO EMRO and UMLF. The search interface changes according to the language selected which allows search terms to be entered in the native language. The user can limit the search output according to the language of publication but citations retrieved are in English only. Links may be provided to journals if published online. Evaluation of the French and Spanish versions using journal key words and a list of common diseases showed 77.5% and 86.5% accuracy respectively. User feedback was positive. PICO Linguist and BabelMeSH could be useful and convenient tools in finding current evidence sources in the medical literature especially for non-English medical terms that may be difficult to express in English.

Besides precision & recall: exploring alternative approaches to evaluating an automatic indexing tool for MEDLINE.

A Neveol — 2007-10-02T12:09:48-00:00

AMIA Annu Symp Proc (2006), pp. 589-593.

OBJECTIVE: This paper explores alternative approaches for the evaluation of an automatic indexing tool for MEDLINE, complementing the traditional precision and recall method. MATERIALS AND METHODS: The performance of MTI, the Medical Text Indexer used at NLM to produce MeSH recommendations for biomedical journal articles is evaluated on a random set of MEDLINE citations. The evaluation examines semantic similarity at the term level (indexing terms). In addition, the documents retrieved by queries resulting from MTI index terms for a given document are compared to the PubMed related citations for this document. RESULTS: Semantic similarity scores between sets of index terms are higher than the corresponding Dice similarity scores. Overall, 75% of the original documents and 58% of the top ten related citations are retrieved by queries based on the automatic indexing. CONCLUSIONS: The alternative measures studied in this paper confirm previous findings and may be used to select particular documents from the test set for a more thorough analysis.

A Document Clustering and Ranking System for Exploring MEDLINE Citations

Yongjing Lin — 2007-10-02T11:34:46-00:00

J Am Med Inform Assoc, Vol. 14, No. 5. (1 September 2007), pp. 651-661.

ObjectiveA major problem faced in biomedical informatics involves how best to present information retrieval results. When a single query retrieves many results, simply showing them as a long list often provides poor overview. With a goal of presenting users with reduced sets of relevant citations, this study developed an approach that retrieved and organized MEDLINE citations into different topical groups and prioritized important citations in each group. DesignA text mining system framework for automatic document clustering and ranking organized MEDLINE citations following simple PubMed queries. The system grouped the retrieved citations, ranked the citations in each cluster, and generated a set of keywords and MeSH terms to describe the common theme of each cluster. MeasurementsSeveral possible ranking functions were compared, including citation count per year (CCPY), citation count (CC), and journal impact factor (JIF). We evaluated this framework by identifying as "important" those articles selected by the Surgical Oncology Society. ResultsOur results showed that CCPY outperforms CC and JIF, i.e., CCPY better ranked important articles than did the others. Furthermore, our text clustering and knowledge extraction strategy grouped the retrieval results into informative clusters as revealed by the keywords and MeSH terms extracted from the documents in each cluster. ConclusionsThe text mining system studied effectively integrated text clustering, text summarization, and text ranking and organized MEDLINE retrieval results into different topical groups. 10.1197/jamia.M2215

MEDLINE as a source of just-in-time answers to clinical questions.

D Demner-Fushman — 2007-10-01T06:58:25-00:00

AMIA Annu Symp Proc (2006), pp. 190-194.

Clinicians increasingly use handheld devices to support evidence-based practice and for clinical decision support. However, support of clinical decisions through information retrieval from MEDLINE(R) and other databases lags behind popular daily activities such as patient information or drug formulary look-up. The objective of the current study is to determine whether relevant information can be retrieved from MEDLINE to answer clinical questions using a handheld device at the point of care. Analysis of search and retrieval results for 108 clinical questions asked by members of clinical teams during 28 daily rounds in a 12-bed intensive care unit confirm MEDLINE as a potentially valuable resource for just-in-time answers to clinical questions. Answers to 93 (86%) questions were found in MEDLINE by two resident physicians using handheld devices. The majority of answers, 88.9% and 97.7% respectively, were found during rounds. Strategies that facilitated timely retrieval of results include using PubMed(R) Clinical Queries and Related Articles, spell check, and organizing retrieval results into topical clusters. Further possible improvements in organization of retrieval results such as automatic semantic clustering and providing patient outcome information along with the titles of the retrieved articles are discussed.

Prospective validation of text categorization filters for identifying high-quality, content-specific articles in MEDLINE.

Y Aphinyanaphongs — 2007-10-01T06:57:38-00:00

AMIA Annu Symp Proc (2006), pp. 6-10.

In prior work, we introduced a machine learning method to identify high quality MEDLINE documents in internal medicine. The performance of the original filter models built with this corpus on years outside 1998-2000 was not assessed directly. Validating the performance of the original filter models on current corpora is crucial to validate them for use in current years, to verify that the model fitting and model error estimation procedures do not over-fit the models, and to validate consistency of the chosen ACPJ gold standard (i.e., that ACPJ editorial policies and criteria are stable over time). Our prospective validation results indicated that in the categories of treatment, etiology, diagnosis, and prognosis, the original machine learning filter models built from the 1998-2000 corpora maintained their discriminatory performance of 0.97, 0.97, 0.94, and 0.94 area under the curve in each respective category when applied to a 2005 corpus. The ACPJ is a stable, reliable gold standard and the machine learning methodology provides robust models and model performance estimates. Machine learning filter models built with 1998-2000 corpora can be applied to identify high quality articles in recent years.

Is MEDLINE alone enough for a meta-analysis?

Bai — 2007-06-10T08:04:20-00:00

Alimentary Pharmacology & Therapeutics, Vol. 26, No. 1. (July 2007), pp. 125-126.

[Public scientific knowledge distribution in health information, communication and information technology indexed in MEDLINE and LILACS databases]

AL Packer — 2007-09-27T07:25:38-00:00

Cien Saude Colet, Vol. 12, No. 3. (n 2007), pp. 587-599.

This study explores the distribution of international, regional and national scientific output in health information and communication, indexed in the MEDLINE and LILACS databases, between 1996 and 2005. A selection of articles was based on the hierarchical structure of Information Science in MeSH vocabulary. Four specific domains were determined: health information, medical informatics, scientific communications on healthcare and healthcare communications. The variables analyzed were: most-covered subjects and journals, author affiliation and publication countries and languages, in both databases. The Information Science category is represented in nearly 5% of MEDLINE and LILACS articles. The four domains under analysis showed a relative annual increase in MEDLINE. The Medical Informatics domain showed the highest number of records in MEDLINE, representing about half of all indexed articles. The importance of Information Science as a whole is more visible in publications from developed countries and the findings indicate the predominance of the United States, with significant growth in scientific output from China and South Korea and, to a lesser extent, Brazil.

The pitfalls of a systematic MEDLINE review in palliative medicine: symptom assessment instruments.

N O'Leary — 2007-09-21T07:29:16-00:00

Am J Hosp Palliat Care, Vol. 24, No. 3. (l 2007), pp. 181-184.

The Medical Literature Analysis and Retrieval System Online (MEDLINE) database provides many references for reviews, but many relevant articles are missed, especially when the topic is complex. Reported here is the detailed methodology of a PubMed search of MEDLINE augmented by a related articles link search. Of 1181 citations identified, through a PubMed search, 10 articles met the inclusion criteria. Fifty-one were identified through the related articles link; of which 43 were not detected by standard searches using medical subject heading terms. More than 50% were identified using the related articles link. Only 14% of relevant articles were identified using the standard PubMed MEDLINE search. The related articles link is not included in methodologic recommendations for systematic literature reviews but this experience suggests that it is a useful tool in PubMed for reviewing complex evidence. Related links searches are proposed in any systematic PubMed MEDLINE literature review in palliative medicine.

The sensitivity and precision of search terms in Phases I, II and III of the Cochrane Highly Sensitive Search Strategy for identifying reports of randomized trials inmedlinein a specific area of health careHIV/AIDS prevention and treatment interventions

Eisinga — 2007-06-24T00:09:22-00:00

Health Information and Libraries Journal, Vol. 24, No. 2. (June 2007), pp. 103-109.

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

Maksim Plikus — 2006-10-03T03:18:50-00:00

BMC Bioinformatics, Vol. 7 (02 October 2006), 424.

A MEDLINE categorization algorithm.

SJ Darmoni — 2007-09-10T09:14:31-00:00

BMC Med Inform Decis Mak, Vol. 6 (2006)

BACKGROUND: Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. METHODS: The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. RESULTS: The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. CONCLUSION: We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms/subheadings) pairs by NLM indexers. This algorithm may be used as a new bibliometric tool.

How to select publications on occupational health: the usefulness of Medline and the impact factor

JF Gehanno — 2007-09-10T09:03:01-00:00

Occup Environ Med, Vol. 57, No. 10. (1 October 2000), pp. 706-709.

OBJECTIVES[---]Publications in the field of occupational health appear in various journals, including those of other medical specialties. This complicates the follow up of literature for specialists in this field. On the basis of Medline and the impact factor, this diversity was assessed, and a cost effective method for selecting the most pertinent journals in the practice of occupational health was proposed. METHODS[---]A Medline search identified all the articles published in 1998 with occupational diseases or occupational exposures as the main topic. These articles were classified based on the journals in which they appeared. The journals were then compared according to their subject area, the number of articles that were published in the fields studied, and their impact factor. RESULTS[---]The search retrieved 2247 articles, published in 577 different journals in 1998. Each journal published between one and 105 articles during this period (mean 3.89). However, only 1.4% of the journals accounted for more than 25% of the total articles published. More than half of the articles were published in journals dealing with general practice or medical specialties other than occupational health. Only 66% of retrieved journals had an impact factor, and more than 80% of the articles were published in journals with an impact factor <2. CONCLUSION[---]Simply following up occupational health journals is not sufficient to meet the requirements of the occupational health professional. Moreover, the use of the impact factor cannot be considered as a reliable research tool to assess follow up. Two lists of eight and 38 journals were thus set up. They permit a literature coverage of 27% and 52% respectively in the specific fields studied, and this seems to be the optimal compromise between time and literature covered. Lastly, practical procedures are suggested to follow up literature and obtain abstracts from selected journals on the internet. 10.1136/oem.57.10.706

A study comparing centralized CD-ROM and decentralized intranet access to MEDLINE.

SJ Darmoni — 2007-09-10T09:02:35-00:00

Bull Med Libr Assoc, Vol. 88, No. 2. (April 2000), pp. 152-156.

OBJECTIVE: The purpose of this study was to evaluate the efficacy of a decentralized intranet access in each medical department as opposed to centralized unique MEDLINE access in the medical library. DESIGN: A two-phase questionnaire to evaluate MEDLINE use was given to junior and senior physicians at Rouen University Hospital (RUH). Phase I (August-October 1996) corresponded to a time period when centralized access was the only means of access available and phase II (August-October 1997) to a time period following the introduction of decentralized intranet access. RESULTS: A total of 168 physicians filled out at least one phase of the questionnaire, among whom 123 (73%) filled out both phases. Use of MEDLINE significantly increased in 1997 (average of 10.2+/-1.1 searches in three months) versus 1996 (average of 4.9+/-0.7 searches in three months, P<0.0001). The aim of searches changed, becoming significantly more care oriented in phase II (P<0.0001). The number of searches performed by the physicians alone increased (P<0.0001) and searches performed by the librarian decreased (P<0.0001) in phase II. The method of searches also changed, as searches by author (P< 0.0001), by journal (P = 0.0042), and by free word (P = 0.0027) increased in phase II. Knowledge of the following concepts of MEDLINE significantly increased: explosion (P<0.0001), scope note (P<0.0001), Abridged Index Medicus (AIM) journals (P<0.0001), Medical Subject Headings (MeSH) qualifier (P<0.0001), and focus (P<0.0001). CONCLUSION: A decentralized intranet access to MEDLINE increased the number of searches and knowledge of this bibliographic database. MEDLINE intranet access modified the purpose and the methods of searching.

Costs of medline and CD-ROM searching.

B Thirion — 2007-09-10T08:55:00-00:00

Lancet, Vol. 340, No. 8814. (1 August 1992)

The value of using verbs in Medline searches.

V Bertaud — 2007-09-10T08:35:50-00:00

Med Inform Internet Med, Vol. 32, No. 2. (June 2007), pp. 117-122.

New findings are continuously identified thanks to novel diagnostic procedures, among others in medical imaging. It would be useful to retrieve these new findings from literature. The aim of this work is to investigate if using verbs in MEDLINE queries can improve the retrieval of findings. Verbs used in the field of findings were selected: 'to show' (an examination shows a finding) and 'to confirm' (a finding confirms a diagnosis). For each of these verbs, semantically close verbs were researched on the WordNet website. Then, the extent to which adding these verbs to a query about various radiological pathologies can improve findings retrieval in Medline citations was studied. This method has been tested on two sets of MEDLINE citations regarding the diagnostic imaging of musculo-skeletal disorders. Using appropriate verbs in Medline queries enhances the precision from 53% to 61% and from 53% to 74%, respectively, in our first and second test set. A recall of 74% and 83% was reached in our two experiments. Using relevant verbs can be a rather simple way to improve the retrieval of findings related to diseases and diagnostic procedures from Medline citations.

OReFiL: an online resource finder for life sciences

Yasunori Yamamoto — 2007-08-06T06:44:13-00:00

BMC Bioinformatics, Vol. 8 (06 August 2007), 287.