Recent research for MEDLINE/PubMed: short review
26 Oct 2010-pp 69-70
TL;DR: Recent information retrieval research for MEDLINE and its information retrieval system PubMed is discussed by reviewing eight recent papers from different areas: improving and optimizing the user's query, user behavior, and comparison of different search techniques.
Abstract: MEDLINE is the largest biomedical bibliographic database in the world. In this paper we discuss recent information retrieval research for MEDLINE and its information retrieval system PubMed by reviewing eight recent papers from different areas: improving and optimizing the user's query, user behavior, and comparison of different search techniques.
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TL;DR: This study sheds light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log and found that experienced PubMed users who use system functions quickly retrieve relevant documents have longer search sessions than experienced users.
Abstract: Background: PubMed is the largest biomedical bibliographic information source on the Internet. PubMed has been considered one of the most important and reliable sources of up-to-date health care evidence. Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed. However, very little is known about PubMed users’ knowledge of information retrieval (IR) functions and their usage in query formulation. Objective: The purpose of this study was to shed light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log. Our hypotheses were that (1) experienced PubMed users who use system functions quickly retrieve relevant documents and (2) nonexperienced PubMed users who do not use them have longer search sessions than experienced users. Methods: To test these hypotheses, we analyzed PubMed query log data containing nearly 3 million queries. User sessions were divided into two categories: experienced and nonexperienced. We compared experienced and nonexperienced users per number of sessions, and experienced and nonexperienced user sessions per session length, with a focus on how fast they completed their sessions. Results: To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5. The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups. Conclusions: Experienced PubMed users retrieve relevant documents more quickly than nonexperienced PubMed users in terms of session length. [JMIR Med Inform 2015;3(3):e25]
30 citations
Cites background from "Recent research for MEDLINE/PubMed:..."
...For example, PubMed, which is maintained by the United States National Library of Medicine (NLM), is one of the largest and most authoritative online biomedical bibliographic databases in the world [10-12]....
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TL;DR: 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.
Abstract: 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.
25 citations
Cites background from "Recent research for MEDLINE/PubMed:..."
...PubMed/MEDLINE, maintained by the National Library of Medicine (NLM), is one of the largest and freely available biomedical bibliographic databases in the world [4-7] and considered as one of the most important and...
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TL;DR: In this article, the authors propose a method to solve the problem of homonymity in homonymization, i.e., homonymisation of homonyms.s.s 254
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4 citations
TL;DR: The US PubMed Central and Europe PMC are used as a role model to inform the concept and opportunity for an Australasia open access biomedical repository and the opportunities for futureopen access biomedical repositories are explored.
Abstract: Scholarly publishing has undergone major changes over the past 50 years. Funder mandates and organisational reporting obligations have heralded the creation of open access repositories, such as institutional and subject repositories. This research draws upon the US PubMed Central (PMC) and Europe PMC, also known as PMC International, as a role model to inform the concept and opportunity for an Australasia open access biomedical repository. PMC International is a leader in making citations and research output, which link to research data, Findable, Accessible, Interoperable and Reusable (FAIR). As repositories approach two decades of development, this paper reports on the potential for an Australasia open access biomedical repository through a knowledge management lens and explores the opportunities for future open access biomedical repositories.
2 citations
References
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TL;DR: This work test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE, a database that has each name on each article assigned to one of 6.7 million inferred author-individual clusters.
Abstract: Background: We recently described “Author-ity,” a model for estimating the probability that two articles in MEDLINE, sharing the same author name, were written by the same individual. Features include shared title words, journal name, coauthors, medical subject headings, language, affiliations, and author name features (middle initial, suffix, and prevalence in MEDLINE). Here we test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE. Methods: Enhancements include: (a) incorporating first names and their variants, email addresses, and correlations between specific last names and affiliation words; (b) new methods of generating large unbiased training sets; (c) new methods for estimating the prior probability; (d) a weighted least squares algorithm for correcting transitivity violations; and (e) a maximum likelihood based agglomerative algorithm for computing clusters of articles that represent inferred author-individuals. Results: Pairwise comparisons were computed for all author names on all 15.3 million articles in MEDLINE (2006 baseline), that share last name and first initial, to create Author-ity 2006, a database that has each name on each article assigned to one of 6.7 million inferred author-individual clusters. Recall is estimated at ∼98.8p. Lumping (putting two different individuals into the same cluster) affects ∼0.5p of clusters, whereas splitting (assigning articles written by the same individual to >1 cluster) affects ∼2p of articles. Impact: The Author-ity model can be applied generally to other bibliographic databases. Author name disambiguation allows information retrieval and data integration to become person-centered, not just document-centered, setting the stage for new data mining and social network tools that will facilitate the analysis of scholarly publishing and collaboration behavior. Availability: The Author-ity 2006 database is available for nonprofit academic research, and can be freely queried via http://arrowsmith.psych.uic.edu.
286 citations
"Recent research for MEDLINE/PubMed:..." refers background in this paper
...[6] Torvik, V.I., Smalheiser, N.R. 2009....
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...Torvik and Smalheiser [6] proposed a model for author name disambiguation....
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...Torvik and Smalheiser [6] proposed a model for author name disambiguation....
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...About 2/3 of the authors have last name and first name initials shared by other authors and more than 1/5 of the authors have at least two articles where their name and initials are recorded differently [6]....
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TL;DR: 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, which provided insight into PubMed users’ needs and their behavior.
Abstract: 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.
272 citations
Journal Article•
TL;DR: Comparisons of PubMed and Google Scholar search results for clinical topics in respiratory care to that of a benchmark suggest that PubMed searches with the Clinical Queries filter are more precise than with the Advanced Scholar Search in Google Scholar for respiratory care topics.
Abstract: BACKGROUND: Literature searches are essential to evidence-based respiratory care. To conduct literature searches, respiratory therapists rely on search engines to retrieve information, but there is a dearth of literature on the comparative efficiencies of search engines for researching clinical questions in respiratory care. OBJECTIVE: To compare PubMed and Google Scholar search results for clinical topics in respiratory care to that of a benchmark. METHODS: We performed literature searches with PubMed and Google Scholar, on 3 clinical topics. In PubMed we used the Clinical Queries search filter. In Google Scholar we used the search filters in the Advanced Scholar Search option. We used the reference list of a related Cochrane Collaboration evidence-based systematic review as the benchmark for each of the search results. We calculated recall (sensitivity) and precision (positive predictive value) with 2 2 contingency tables. We compared the results with the chi-square test of independence and Fisher’s exact test. RESULTS: PubMed and Google Scholar had similar recall for both overall search results (71% vs 69%) and full-text results (43% vs 51%). PubMed had better precision than Google Scholar for both overall search results (13% vs 0.07%, P < .001) and full-text results (8% vs 0.05%, P < .001). CONCLUSIONS: Our results suggest that PubMed searches with the Clinical Queries filter are more precise than with the Advanced Scholar Search in Google Scholar for respiratory care topics. PubMed appears to be
103 citations
"Recent research for MEDLINE/PubMed:..." refers background in this paper
...REFERENCES [1] Anders, M.E., Evans, D.P. 2010....
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...Recent PubMed Applications PubMed and MEDLINE are used on daily basis by millions of users whose needs vary widely: information for research purposes, answering clinical questions, teaching medical students, etc. Anders and Evans [1] performed comparison between PubMed and Google Scholar literature searches in the area of evidencebased respiratory care....
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...Anders and Evans [1] performed comparison between PubMed and Google Scholar literature searches in the area of evidencebased respiratory care....
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TL;DR: Investigation of the performance of two search strategies in the retrieval of information from the National Library of Medicine on otolaryngology–head and neck surgery related conditions and diagnoses using PubMed found them to be inadequate.
Abstract: Objective/Hypothesis: This study was conducted to investigate the performance of two search strategies in the retrieval of information from the National Library of Medicine (NLM) on otolaryngology–head and neck surgery related conditions and diagnoses using PubMed. Methods: Two search strategies—one based on the use of Medical Subject Headings (MeSH) and the second based on text word searching—were compared. Results: The MeSH search provided a more efficient search than the text word search. Conclusions: Head and neck surgeons can most efficiently search the NLM using PubMed as a search engine by initiating the search with MeSH terms. Once a key article is identified, the searcher should use the “Related Articles” feature.
71 citations
TL;DR: It is hypothesize, based on protein annotations, that zinc and retinoic acid may play a role in migraine, and the ChemoText repository has promise as a data source for drug discovery.
66 citations
"Recent research for MEDLINE/PubMed:..." refers background in this paper
...Baker and Hemminger [2] proposed a ChemoText system for Literature-based discovery (LBD) that analyzes connections among chemicals, proteins and diseases in order to infer drugdisease connections from MEDLINE....
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...Baker and Hemminger [2] proposed a ChemoText system for Literature-based discovery (LBD) that analyzes connections among chemicals, proteins and diseases in order to infer drugdisease connections from MEDLINE....
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...[2] Baker, N.C., Hemminger, B.M. 2010....
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