Biomedical Journal Articles Research Articles

A quest to increase safety of anesthetics by advancements in anesthesia monitoring: scientometric analysis.

The aim of this study was to assess progress in the field of anesthesia monitoring over the past 40 years using scientometric analysis. The following scientometric indexes were used: popularity indexes (general and specific), representing the proportion of articles on either a topic relative to all articles in the field of anesthetics (general popularity index, GPI) or the subfield of anesthesia monitoring (specific popularity index, SPI); index of change (IC), representing the degree of growth in publications on a topic from one period to the next; and index of expectations (IE), representing the ratio of the number of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed. Publications on 33 anesthesia-monitoring topics were assessed. Our analysis showed that over the past 40 years, the rate of rise in the number of articles on anesthesia monitoring was exponential, with an increase of more than eleven-fold, from 296 articles over the 5-year period 1974–1978 to 3,394 articles for 2009–2013. This rise profoundly exceeded the rate of rise of the number of articles on general anesthetics. The difference was especially evident with the comparison of the related GPIs: stable growth of the GPI for anesthesia monitoring vs constant decline in the GPI for general anesthetics. By the 2009–2013 period, among specific monitoring topics introduced after 1980, the SPI index had a meaningful magnitude (≥1.5) in 9 of 24 topics: Bispectral Index (7.8), Transesophageal Echocardiography (4.2), Electromyography (2.8), Pulse Oximetry (2.4), Entropy (2.3), Train-of-four (2.3), Capnography (1.9), Pulse Contour (1.9), and Electrical Nerve Stimulation for neuromuscular monitoring (1.6). Only one of these topics (Pulse Contour) demonstrated (in 2009–2013) high values for both IC and IE indexes (76 and 16.9, respectively), indicating significant recent progress. We suggest that rapid growth in the field of anesthetic monitoring was one of the most important developments to compensate for the intrinsically low margins of safety of anesthetic agents.

Crowdsourcing for Medical Image Classification

To help manage the large amount of biomedical images produced, image information retrieval tools have been developed to help access the right information at the right moment. To provide a test bed for image retrieval evaluation, the ImageCLEFmed benchmark proposes a biomedical classification task that automatically focuses on determining the image modality of figures from biomedical journal articles. In the training data for this machine learning task, some classes have many more images than others and thus a few classes are not well represented, which is a challenge for automatic image classification. To address this problem, an automatic training set expansion was first proposed. To improve the accuracy of the automatic training set expansion, a manual verification of the training set is done using the crowdsourcing platform Crowdflower. This platform allows the use of external persons to pay for the crowdsourcing or to use personal contacts free of charge. Crowdsourcing requires strict quality control or using trusted persons but it can quickly give access to a large number of judges and thus improve many machine learning tasks. Results show that the manual annotation of a large amount of biomedical images carried out in this project can help with image classification.

Scientometric assessment of drugs for chronic pain, 1979-2013: rapid growth of publications, paucity of successful drugs.

The aim of this study was to find signs of progress in the pharmacotherapy of chronic pain over the past 35 years using scientometric analysis. The following scientometric indices were used: 1) popularity index, representing the share of articles on a specific drug(s) relative to all articles in the field of chronic pain; 2) index of change, representing the degree of growth in publications on a topic from one period to the next; 3) index of expectations, representing the ratio of the number of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed; and 4) index of ultimate success, representing a publication outcome when a new drug takes the place of a common drug previously used for the same purpose. Publications on 55 drugs used in the treatment of chronic pain were assessed during seven 5-year periods, from 1979 to 2013. The rate of rise in the number of publications on chronic pain was exponential, with an increase of nearly ninefold from 2,346 articles over the 5-year period 1979–1983 to 21,095 articles in 2009–2013. However, despite this huge increase in publications, our scientometric analysis did not reveal signs of really successful drugs in this field. For the 2009–2013 period, the popularity index had a meaningful magnitude (from 0.5–2.8) for only 13 of 55 drugs. Five of them were opioids, including morphine, which had the highest index value of all drugs (2.8). None of the drugs had a high index of expectations in 2009–2013. The index of ultimate success was positive only with triptans in the relatively limited area of acute treatment of migraine. As a result, despite rapid growth in the number of publications, our scientometric analysis did not reveal signs of substantial progress in the field of pharmacotherapy for chronic pain.

Descriptions and interpretations of the ACCORD-Lipid trial in the news and biomedical literature: a cross-sectional analysis.

The lipid component of the Action to Control Cardiovascular Risk in Diabetes (ACCORD-Lipid) trial was a landmark, publicly funded study demonstrating that fenofibrate, when added to statin therapy, was not associated with improved cardiovascular outcomes among patients with diabetes mellitus. We performed a cross-sectional study of all articles describing the results of ACCORD-Lipid in the news and biomedical literature in the 15 months following its publication. For articles published in biomedical journals, we determined whether there was an association between authors' conflicts of interest and trial interpretation. We identified 67 news articles and 141 biomedical journal articles discussing ACCORD-Lipid. Approximately 30% of news and biomedical journal articles described fenofibrate as ineffective, whereas nearly 20% concluded it was effective. Among articles making a recommendation, approximately 50% of news and 67% of biomedical journal articles supported continued fibrate use. Authors with conflicts of interest were more likely to describe fenofibrate as effective (27.1% vs 8.9%; relative risk, 3.03; 95% CI, 1.22-7.50; P = .008) and support continued fibrate use (77.4% vs 45.8%; 1.69; 1.07-2.67; P = .006). The ACCORD-Lipid trial was described inconsistently in news and biomedical journal articles, possibly creating uncertainty among patients and physicians. In addition, conflicts of interest were associated with more favorable trial interpretation.

No evidence of real progress in treatment of acute pain, 1993-2012: scientometric analysis.

Over the past 2 decades, many new techniques and drugs for the treatment of acute pain have achieved widespread use. The main aim of this study was to assess the progress in their implementation using scientometric analysis. The following scientometric indices were used: 1) popularity index, representing the share of articles on a specific technique (or a drug) relative to all articles in the field of acute pain; 2) index of change, representing the degree of growth in publications on a topic compared to the previous period; and 3) index of expectations, representing the ratio of the number of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed. Publications on specific topics (ten techniques and 21 drugs) were assessed during four time periods (1993–1997, 1998–2002, 2003–2007, and 2008–2012). In addition, to determine whether the status of routine acute pain management has improved over the past 20 years, we analyzed surveys designed to be representative of the national population that reflected direct responses of patients reporting pain scores. By the 2008–2012 period, popularity index had reached a substantial level (≥5%) only with techniques or drugs that were introduced 30–50 years ago or more (epidural analgesia, patient-controlled analgesia, nerve blocks, epidural analgesia for labor or delivery, bupivacaine, and acetaminophen). In 2008–2012, promising (although modest) changes of index of change and index of expectations were found only with dexamethasone. Six national surveys conducted for the past 20 years demonstrated an unacceptably high percentage of patients experiencing moderate or severe pain with not even a trend toward outcome improvement. Thus, techniques or drugs that were introduced and achieved widespread use for acute pain management within the past 20 years have produced no changes in scientometric indices that would indicate real progress and have failed to improve national outcomes for relief of acute pain. Two possible reasons for this are discussed: 1) the difference between the effectiveness of old and new techniques is not clinically meaningful; and 2) resources necessary for appropriate use of new techniques in routine pain management are not adequate.

Introduction to biomedical literature text mining: context and objectives.

If you are reading this, you know how important it is and almost certainly look to the biomedical literature for a large part of the information you need. We work hard to find more and more biomedical literature, seeking new content from multiple sources. But, can there be too much of a good thing? Most science is reductionist by nature. It is difficult enough finding the relevant nuggets of information from 1,000 documents. It is at least ten times harder to do so from 10,000 documents. And, with 25 million biomedical journal articles and many times that of other textual information sources, we are faced with significant challenges. In this introduction, we identify some of those challenges to prepare you for the remaining chapters.

A System for Extracting Study Design Parameters from Nutritional Genomics Abstracts

Summary The extraction of study design parameters from biomedical journal articles is an important problem in natural language processing (NLP). Such parameters define the characteristics of a study, such as the duration, the number of subjects, and their profile. Here we present a system for extracting study design parameters from sentences in article abstracts. This system will be used as a component of a larger system for creating nutrigenomics networks from articles in the nutritional genomics domain. The algorithms presented consist of manually designed rules expressed either as regular expressions or in terms of sentence parse structure. A number of filters and NLP tools are also utilized within a pipelined algorithmic framework. Using this novel approach, our system performs extraction at a finer level of granularity than comparable systems, while generating results that surpass the current state of the art.

A system for extracting study design parameters from nutritional genomics abstracts.

The extraction of study design parameters from biomedical journal articles is an important problem in natural language processing (NLP). Such parameters define the characteristics of a study, such as the duration, the number of subjects, and their profile. Here we present a system for extracting study design parameters from sentences in article abstracts. This system will be used as a component of a larger system for creating nutrigenomics networks from articles in the nutritional genomics domain. The algorithms presented consist of manually designed rules expressed either as regular expressions or in terms of sentence parse structure. A number of filters and NLP tools are also utilized within a pipelined algorithmic framework. Using this novel approach, our system performs extraction at a finer level of granularity than comparable systems, while generating results that surpass the current state of the art.

A surname-based patent-related indicator: the contribution of Jewish inventors to US patents

It was found that the surname-based representation of Jewish authors in the top US biomedical journals corresponds to the representation of Jewish Nobel Laureates in Medicine among US laureates: Both of them are almost equally disproportionately high, with the ratio of actual to expected number close to 20 (Kissin, Scientometrics 89:273---280, 2011). The main aim of this study was to determine whether the contribution of Jewish inventors is also disproportionately high. The number of patents (US Patent and Trademark Office database) per thousand persons with the same surname (2000 Census) was determined (index P). Index P was compared with index A, which represents the number of the articles in the top US biomedical journals, and index G, which is based on the representation of a surname in the Google's option "Discussions", reflecting a combination of various business and leisure activities (designed as a negative control). The collective contributions of the 96 Jewish surname groups for each of the above indices were calculated. The ratio of actual to expected number of US patents was found to be disproportionately high--6.1 (p < 0.0001). At the same time, this disproportionality was four-fold lower than that related to biomedical articles (ratio of 6.1 vs. 23.3, p < 0.0001). There was some degree of correlation between index P and index A (r = 0.407, p < 0.0001), but no significant correlation was found between index P and index G. The role of various factors in the observed disproportionalities is discussed. The greater degree of disproportionality with biomedical research articles might be a consequence of traditional Jewish inclination towards occupations in medicine.

An early indicator of drug success: Top Journal Selectivity Index

The Top Journal Selectivity Index (TJSI) is a scientometric index reflecting the potential importance of a new drug. It represents the ratio of the number of all types of articles on a particular drug in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by Medline over the 5 years since the drug’s introduction. The TJSI can be an indicator of a drug’s potential for sustained use: a higher score increases the probability of continuing success.

BioCause: Annotating and analysing causality in the biomedical domain

BackgroundBiomedical corpora annotated with event-level information represent an important resource for domain-specific information extraction (IE) systems. However, bio-event annotation alone cannot cater for all the needs of biologists. Unlike work on relation and event extraction, most of which focusses on specific events and named entities, we aim to build a comprehensive resource, covering all statements of causal association present in discourse. Causality lies at the heart of biomedical knowledge, such as diagnosis, pathology or systems biology, and, thus, automatic causality recognition can greatly reduce the human workload by suggesting possible causal connections and aiding in the curation of pathway models. A biomedical text corpus annotated with such relations is, hence, crucial for developing and evaluating biomedical text mining.ResultsWe have defined an annotation scheme for enriching biomedical domain corpora with causality relations. This schema has subsequently been used to annotate 851 causal relations to form BioCause, a collection of 19 open-access full-text biomedical journal articles belonging to the subdomain of infectious diseases. These documents have been pre-annotated with named entity and event information in the context of previous shared tasks. We report an inter-annotator agreement rate of over 60% for triggers and of over 80% for arguments using an exact match constraint. These increase significantly using a relaxed match setting. Moreover, we analyse and describe the causality relations in BioCause from various points of view. This information can then be leveraged for the training of automatic causality detection systems.ConclusionAugmenting named entity and event annotations with information about causal discourse relations could benefit the development of more sophisticated IE systems. These will further influence the development of multiple tasks, such as enabling textual inference to detect entailments, discovering new facts and providing new hypotheses for experimental work.

The second step towards international society

Just one year ago, I congratulated the changes happened to the Journal of Korean Academy of Conservative Dentistry, the official journal of the Korean Academy of Conservative Dentistry. From the first issue of volume 37 in March 2012, we changed the journal name to Restorative Dentistry and Endodontics (RDE; Restor Dent Endod, standardized abbreviation of the journal suggested by the List of Title Word Abbreviation). We adopted a new and fresh design. At about the same time, RDE was indexed on KoreaMed (http://www.koreamed.org) and KoreaMed Synapse (http://synapse.koreamed.org). Its full text pdf files can be tracked and downloaded from the journal homepage (www.rde.ac) and the KoreaMed Synapse. We have published all the articles in English from the 3rd issue of Volume 37. These changes were the first step of the RDE towards the international society. The changes were initiated by the leadership of former president Professor Seung-Ho Baek, and were succeeded by the present president Professor Sung-Kyo Kim. On the first day of 2010, we initiated internationalization of the official journal of the Korean Academy of Conservative Dentistry. We organized a working committee for internationalization of RDE, opened our English journal homepage (www.rde.ac), invited foreign experts as Editorial Members and reviewers, and improved the editorial system. Within a year from the first step, we have achieved a great success for international communication. RDE is now proud to participate in PubMed and PubMed Central (PMC). RDE has platforms for world-wide communication. PMC is a free digital database of full-text literature in biomedical and life science, which was developed as an online archive of biomedical journal articles by the U.S. National Library of Medicine (NLM). Now, RDE is fully covered by KoreaMed, Synapse, KoMCI, CrossRef, Google Scholar, PubMed, and PMC. RDE must have been on the second step towards international society. We are renewing the editorial process and the journal homepage for convenience of the foreign contributors. We hope RDE to be known world-wide by dentists and researchers. We hope RDE contribute to the oral health care of mankind. I really appreciate the members of the working committee devoting themselves to improving RDE. I also appreciate the Korean Association of Medical Journal Editors (KAMJE) and XMLink leading RDE to PMC. Additionally, I would like to express my appreciation to the board members, the president, and all the members of KACD for their support for our journal. Byeong-Hoon Cho, Editor-in-Chief Vol. 38, No. 1, 2013

Concept annotation in the CRAFT corpus.

BackgroundManually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text.ResultsThis paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and syntactically to serve as a research resource for the biomedical natural-language-processing (NLP) community. CRAFT identifies all mentions of nearly all concepts from nine prominent biomedical ontologies and terminologies: the Cell Type Ontology, the Chemical Entities of Biological Interest ontology, the NCBI Taxonomy, the Protein Ontology, the Sequence Ontology, the entries of the Entrez Gene database, and the three subontologies of the Gene Ontology. The first public release includes the annotations for 67 of the 97 articles, reserving two sets of 15 articles for future text-mining competitions (after which these too will be released). Concept annotations were created based on a single set of guidelines, which has enabled us to achieve consistently high interannotator agreement.ConclusionsAs the initial 67-article release contains more than 560,000 tokens (and the full set more than 790,000 tokens), our corpus is among the largest gold-standard annotated biomedical corpora. Unlike most others, the journal articles that comprise the corpus are drawn from diverse biomedical disciplines and are marked up in their entirety. Additionally, with a concept-annotation count of nearly 100,000 in the 67-article subset (and more than 140,000 in the full collection), the scale of conceptual markup is also among the largest of comparable corpora. The concept annotations of the CRAFT Corpus have the potential to significantly advance biomedical text mining by providing a high-quality gold standard for NLP systems. The corpus, annotation guidelines, and other associated resources are freely available at http://bionlp-corpora.sourceforge.net/CRAFT/index.shtml.

Desiderata for ontologies to be used in semantic annotation of biomedical documents

A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities.

Configuring users of cholesterol lowering foods: A review of biomedical discourse

This paper explores how users of foods containing phytosterols are 'configured' within biomedical research and writing on these substances. A growing range of such foods have been launched and marketed on the basis that they actively lower cholesterol. They are among the most prominent examples of a set of foods designated as 'functional foods'. The paper is based on an analysis of biomedical journal articles which address the use of phytosterols as a cholesterol lowering agent in humans. These include both original research papers and commentaries such as review articles, letters, editorials, news items and professional guidelines. My analysis suggests that users are constituted variously as autonomous, self-motivated consumers, patients and publics needing advice, people resistant to pill use, and practitioners looking for something to offer their patients. I characterise the imagined uses of the products as healthy/holistic, lazy/busy/contemporary, and incompetent use. These varying portrayals of users and their use of these food products entail different ways of understanding health identities and different allocations of responsibilities between the technology, user and health care professionals. I conclude that, while experts and regulators may attempt to configure 'correct' uses of these products, relatively little is known about the rationales and practices of actual users.

Using the Gene Ontology to Annotate Biomedical Journal Articles

We are creating a gold-standard corpus of manually annotated full-text biomedical journal articles toward natural-language-processing applications. Central to this is our use of entire ontologies of the Open Biomedical Ontologies initiative as well as other terminologies as term sources, in contrast to most other such annotation projects, which have used small, ad hoc schemas. In addition to the standard difficulties in such annotation projects, each of the terminologies we have used has idiosyncrasies and ambiguities that present further challenges to consistent, high-quality annotation of these articles. In this paper we present and discuss the most salient of these with regard to the Gene Ontology that we have encountered and addressed in our annotation guidelines and training. The utility of these guidelines can be seen in the high and still-increasing interannotator-agreement statistics that we continually monitor.

Using the Gene Ontology to Annotate Biomedical Journal Articles

AbstractWe are creating a gold-standard corpus of manually annotated full-text biomedical journal articles toward natural-language-processing applications. Central to this is our use of entire ontologies of the Open Biomedical Ontologies initiative as well as other terminologies as term sources, in contrast to most other such annotation projects, which have used small, ad hoc schemas. In addition to the standard difficulties in such annotation projects, each of the terminologies we have used has idiosyncrasies and ambiguities that present further challenges to consistent, high-quality annotation of these articles. In this paper we present and discuss the most salient of these with regard to the Gene Ontology that we have encountered and addressed in our annotation guidelines and training. The utility of these guidelines can be seen in the high and still-increasing interannotator-agreement statistics that we continually monitor.

Dependency Pattern Models for Information Extraction

Several techniques for the automatic acquisition of Information Extraction (IE) systems have used dependency trees to form the basis of an extraction pattern representation. These approaches have used a variety of pattern models (schemes for representing IE patterns based on particular parts of the dependency analysis). An appropriate pattern model should be expressive enough to represent the information which is to be extracted from text without being overly complex. Previous investigations into the appropriateness of the currently proposed models have been limited. This paper compares a variety of pattern models, including ones which have been previously reported and variations of them. Each model is evaluated using existing data consisting of IE scenarios from two very different domains (newswire stories and biomedical journal articles). The models are analysed in terms of their ability to represent relevant information, number of patterns generated and performance on an IE scenario. It was found that the best performance was observed from two models which use the majority of relevant portions of the dependency tree without including irrelevant sections.

Technical editing of research reports in biomedical journals.

Most journals try to improve their articles by technical editing processes such as proof-reading, editing to conform to 'house styles', grammatical conventions and checking accuracy of cited references. Despite the considerable resources devoted to technical editing, we do not know whether it improves the accessibility of biomedical research findings or the utility of articles. This is an update of a Cochrane methodology review first published in 2003. To assess the effects of technical editing on research reports in peer-reviewed biomedical journals, and to assess the level of accuracy of references to these reports. We searched The Cochrane Library Issue 2, 2007; MEDLINE (last searched July 2006); EMBASE (last searched June 2007) and checked relevant articles for further references. We also searched the Internet and contacted researchers and experts in the field. Prospective or retrospective comparative studies of technical editing processes applied to original research articles in biomedical journals, as well as studies of reference accuracy. Two review authors independently assessed each study against the selection criteria and assessed the methodological quality of each study. One review author extracted the data, and the second review author repeated this. We located 32 studies addressing technical editing and 66 surveys of reference accuracy. Only three of the studies were randomised controlled trials. A 'package' of largely unspecified editorial processes applied between acceptance and publication was associated with improved readability in two studies and improved reporting quality in another two studies, while another study showed mixed results after stricter editorial policies were introduced. More intensive editorial processes were associated with fewer errors in abstracts and references. Providing instructions to authors was associated with improved reporting of ethics requirements in one study and fewer errors in references in two studies, but no difference was seen in the quality of abstracts in one randomised controlled trial. Structuring generally improved the quality of abstracts, but increased their length. The reference accuracy studies showed a median citation error rate of 38% and a median quotation error rate of 20%. Surprisingly few studies have evaluated the effects of technical editing rigorously. However there is some evidence that the 'package' of technical editing used by biomedical journals does improve papers. A substantial number of references in biomedical articles are cited or quoted inaccurately.

Access to Medical Literature

The incorporation of medical library services in an academic library will bring about substantial changes, and should include the review of the impact of this transition on each individual department. The use of electronic systems to request and deliver Interlibrary Loan documents has evolved gradually in the past twenty years, and affects medical libraries in unique ways. The electronic submission, publication and access to biomedical journal articles are still changing constantly, and contribute to new challenges in interlibrary borrowing and lending. This article focuses on new developments. It includes instructions on how a library can prepare to incorporate a new dimension of service in the midst of these changes.