Modeling the co-citation dependence on semantic layers of co-cited documents

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maryam Yaghtin ◽  
Hajar Sotudeh ◽  
Alireza Nikseresht ◽  
Mahdieh Mirzabeigi
Keyword(s):  
Peer Review ◽  
Language Processing ◽  
Opinion Mining ◽  
Citation Network ◽  
Test Collection ◽  
Medical Subject Headings ◽  
Content Type ◽  
Citation Frequency ◽  
Mesh Terms ◽  
Citation Measures

PurposeCo-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige of the co-cited articles. Despite its quantitative nature, it is found effective in retrieving and evaluating documents, signifying its linkage with the related documents' contents. To better understand the dynamism of the citation network, the present study aims to investigate various content features giving rise to the measure.Design/methodology/approachThe present study examined the interaction of different co-citation features in explaining the co-citation frequency. The features include the co-cited works' similarities in their full-texts, Medical Subject Headings (MeSH) terms, co-citation proximity, opinions and co-citances. A test collection is built using the CITREC dataset. The data were analyzed using natural language processing (NLP) and opinion mining techniques. A linear model was developed to regress the objective and subjective content-based co-citation measures against the natural log of the co-citation frequency.FindingsThe dimensions of co-citation similarity, either subjective or objective, play significant roles in predicting co-citation frequency. The model can predict about half of the co-citation variance. The interaction of co-opinionatedness and non-co-opinionatedness is the strongest factor in the model.Originality/valueIt is the first study in revealing that both the objective and subjective similarities could significantly predict the co-citation frequency. The findings re-confirm the citation analysis assumption claiming the connection between the cognitive layers of cited documents and citation measures in general and the co-citation frequency in particular.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/OIR-04-2020-0126.

scholarly journals Trends in biomedical informatics: automated topic analysis of JAMIA articles

2015 ◽  
Vol 22 (6) ◽  
pp. 1153-1163 ◽  
Author(s):  
Dong Han ◽  
Shuang Wang ◽  
Chao Jiang ◽  
Xiaoqian Jiang ◽  
Hyeon-Eui Kim ◽  
...  
Keyword(s):  
Language Processing ◽  
Biomedical Informatics ◽  
Tensor Decomposition ◽  
Medical Subject Headings ◽  
Topic Analysis ◽  
Interdisciplinary Field ◽  
Mesh Terms ◽  
Wide Range ◽  
Number Of Publications ◽  
Number Of Citations

Abstract Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a “generalist” journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods , Organization & Administration , and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years.

scholarly journals Automated literature mining and hypothesis generation through a network of Medical Subject Headings

2018 ◽  
Author(s):  
Stephen Joseph Wilson ◽  
Angela Dawn Wilkins ◽  
Matthew V. Holt ◽  
Byung Kwon Choi ◽  
Daniel Konecki ◽  
...  
Keyword(s):  
Language Processing ◽  
Scientific Literature ◽  
Growth Factor Receptor ◽  
Direct Interaction ◽  
Hypothesis Generation ◽  
Supervised Machine Learning ◽  
Literature Mining ◽  
Cancer Genes ◽  
Medical Subject Headings ◽  
Mesh Terms

ABSTRACTThe scientific literature is vast, growing, and increasingly specialized, making it difficult to connect disparate observations across subfields. To address this problem, we sought to develop automated hypothesis generation by networking at scale the MeSH terms curated by the National Library of Medicine. The result is a Mesh Term Objective Reasoning (MeTeOR) approach that tallies associations among genes, drugs and diseases from PubMed and predicts new ones.Comparisons to reference databases and algorithms show MeTeOR tends to be more reliable. We also show that many predictions based on the literature prior to 2014 were published subsequently. In a practical application, we validated experimentally a surprising new association found by MeTeOR between novel Epidermal Growth Factor Receptor (EGFR) associations and CDK2. We conclude that MeTeOR generates useful hypotheses from the literature (http://meteor.lichtargelab.org/).AUTHOR SUMMARYThe large size and exponential expansion of the scientific literature forms a bottleneck to accessing and understanding published findings. Manual curation and Natural Language Processing (NLP) aim to address this bottleneck by summarizing and disseminating the knowledge within articles as key relationships (e.g. TP53 relates to Cancer). However, these methods compromise on either coverage or accuracy, respectively. To mitigate this compromise, we proposed using manually-assigned keywords (MeSH terms) to extract relationships from the publications and demonstrated a comparable coverage but higher accuracy than current NLP methods. Furthermore, we combined the extracted knowledge with semi-supervised machine learning to create hypotheses to guide future work and discovered a direct interaction between two important cancer genes.

Determining the informativeness of comments: a natural language study of F1000Research open peer review reports

2020 ◽  
Vol 44 (7) ◽  
pp. 1327-1345
Author(s):  
Kianoosh Rashidi ◽  
Hajar Sotudeh ◽  
Mahdieh Mirzabeigi ◽  
Alireza Nikseresht
Keyword(s):  
Natural Language ◽  
Operating Characteristic ◽  
Roc Curves ◽  
Test Collection ◽  
Medical Subject Headings ◽  
Content Type ◽  
Scientific Papers ◽  
Open Review ◽  
Review Reports ◽  
Social Comments

PurposeSocial comments are rich in information and useful in evaluating, ranking or retrieving different kinds of materials. However, their merits in representing or providing added values to scientific articles have not yet been studied. Therefore, the present study investigates the informativeness of open review reports as a kind of social comments in a scholarly setting.Design/methodology/approachA test collection was built consisting of 100 randomly selected queries, 1,962 reviewed documents and their reviewers' open reports from F1000Research. They were analyzed using natural language techniques. The comments' salient words were compared to the documents' and also to the Medical Subject Headings (MeSH) salient words. The receiver operating characteristic (ROC) curve was used to test the accuracy of the comments in representing their related articles.FindingsThe papers' contents and comments have a considerable number of salient words in common. The comments' salient words are also largely found in the MeSH, signifying their consistency with the knowledge tree and their potential to add some complementary features to their related items. The ROC curves confirm the accuracy of the comments in retrieving their related papers.Originality/valueThis research is the first to reveal the merits of open review reports on scientific papers, in terms of their relatedness to their mother articles, in specific, and to the knowledge tree, in general. They are found informative in not only representing the reviewed papers but also in adding values to the contents of the papers.

Liraglutide for the Treatment of Obesity: Analyzing Published Reviews

2019 ◽  
Vol 25 (15) ◽  
pp. 1783-1790 ◽  
Author(s):  
Rosario Pastor ◽  
Josep A. Tur
Keyword(s):  
Weight Loss ◽  
Clinical Trials ◽  
Systematic Reviews ◽  
Randomized Clinical Trials ◽  
Statistical Tests ◽  
Overweight And Obesity ◽  
Cochrane Library ◽  
Medical Subject Headings ◽  
Mesh Terms ◽  
Treatment Of Obesity

Background: Several drugs have been currently approved for the treatment of obesity. The pharmacokinetic of liraglutide, as well as the treatment of type 2 diabetes mellitus, have been widely described. Objective: To analyze the published systematic reviews on the use of liraglutide for the treatment of obesity. Methods: Systematic reviews were found out through MEDLINE searches, through EBSCO host and the Cochrane Library based on the following terms: "liraglutide" as major term and using the following Medical Subject Headings (MesH) terms: "obesity", "overweight", "weight loss". A total of 3 systematic reviews were finally included to be analyzed. Results: From the three systematic reviews selected, only two included the randomized clinical trials, while the third study reviewed both randomized and non-randomized clinical trials. Only one review performed statistical tests of heterogeneity and a meta-analysis, combining the results of individual studies. Another review showed the results of individual studies with odds ratio and confidence interval, but a second one just showed the means and confidence intervals. In all studies, weight loss was registered in persons treated with liraglutide in a dose dependent form, reaching a plateau at 3.0 mg dose, which was reached just in men. Most usual adverse events were gastrointestinal. Conclusion: More powerful and prospective studies are needed to assess all aspects related to liraglutide in the overweight and obesity treatment.

The Role of Leukotrienes Inhibitors in the Management of Chronic Inflammatory Diseases

2020 ◽  
Vol 14 (1) ◽  
pp. 15-31
Author(s):  
Deepak Meshram ◽  
Khushbo Bhardwaj ◽  
Charulata Rathod ◽  
Gail B. Mahady ◽  
Kapil K. Soni
Keyword(s):  
Respiratory Diseases ◽  
Inflammatory Diseases ◽  
Leukotriene B4 ◽  
Published Data ◽  
Free Text ◽  
Plant Origin ◽  
Medical Subject Headings ◽  
Leukotriene Antagonists ◽  
Mesh Terms ◽  
Mediators Of Inflammation

Background: Leukotrienes are powerful mediators of inflammation and interact with specific receptors in target cell membrane to initiate an inflammatory response. Thus, Leukotrienes (LTs) are considered to be potent mediators of inflammatory diseases including allergic rhinitis, inflammatory bowel disease and asthma. Leukotriene B4 and the series of cysteinyl leukotrienes (C4, D4, and E4) are metabolites of arachidonic acid metabolism that cause inflammation. The cysteinyl LTs are known to increase vascular permeability, bronco-constriction and mucus secretion. Objectives: To review the published data for leukotriene inhibitors of plant origin and the recent patents for leukotriene inhibitors, as well as their role in the management of inflammatory diseases. Methods: Published data for leukotrienes antagonists of plant origin were searched from 1938 to 2019, without language restrictions using relevant keywords in both free text and Medical Subject Headings (MeSH terms) format. Literature and patent searches in the field of leukotriene inhibitors were carried out by using numerous scientific databases including Science Direct, PubMed, MEDLINE, Google Patents, US Patents, US Patent Applications, Abstract of Japan, German Patents, European Patents, WIPO and NAPRALERT. Finally, data from these information resources were analyzed and reported in the present study. Results: Currently, numerous anti-histaminic medicines are available including chloropheneremine, brompheniramine, cetirizine, and clementine. Furthermore, specific leukotriene antagonists from allopathic medicines are also available including zileuton, montelukast, pranlukast and zafirlukast and are considered effective and safe medicines as compared to the first generation medicines. The present study reports leukotrienes antagonistic agents of natural products and certain recent patents that could be an alternative medicine in the management of inflammation in respiratory diseases. Conclusion: The present study highlights recent updates on the pharmacology and patents on leukotriene antagonists in the management of inflammation respiratory diseases.

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

Study on high-temperature wear and mechanism of Al-Si/graphite composites prepared by the die-casting process

2020 ◽  
Vol 72 (10) ◽  
pp. 1153-1158 ◽  
Author(s):  
Yafei Deng ◽  
Xiaotao Pan ◽  
Guoxun Zeng ◽  
Jie Liu ◽  
Sinong Xiao ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Wear Rate ◽  
Peer Review ◽  
Die Casting ◽  
Casting Machine ◽  
Injection Pressure ◽  
Casting Process ◽  
Matrix Alloy ◽  
Content Type ◽  
The Matrix

Purpose This paper aims to improve the tribological properties of aluminum alloys and reduce their wear rate. Design/methodology/approach Carbon is placed in the model at room temperature, pour 680°C of molten aluminum into the pressure chamber, and then pressed it into the mold containing carbon felt through a die casting machine, and waited for it to cool, which used an injection pressure of 52.8 MPa and held the same pressure for 15 s. Findings The result indicated that the mechanical properties of matrix and composite are similar, and the compressive strength of the composite is only 95% of the matrix alloy. However, the composite showed a low friction coefficient, the friction coefficient of Gr/Al composite is only 0.15, which just is two-third than that of the matrix alloy. Similarly, the wear rate of the composite is less than 4% of the matrix. In addition, the composite can avoid severe wear before 200°C, but the matrix alloy only 100°C. Originality/value This material has excellent friction properties and is able to maintain this excellent performance at high temperatures. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0454/

Socioeconomic effects of pension spending: evidence from Spain

2020 ◽  
Vol 47 (5) ◽  
pp. 599-617
Author(s):  
Fernando Bermejo ◽  
Eladio Febrero ◽  
Andre Fernandes Tomon Avelino
Keyword(s):  
Peer Review ◽  
Social Protection ◽  
Pension System ◽  
Decomposition Analysis ◽  
Value Added ◽  
Total Output ◽  
Alternative View ◽  
Input Output ◽  
Structural Decomposition Analysis ◽  
Content Type

PurposeThe purpose of this study is to provide broader understanding of the significant role that the pension system has in the Spanish economy by estimating the sectoral production, employment and income sustained by pensioners' consumption.Design/methodology/approachBased on input–output tables by the World Input–Output Database and consumption data from the Household Budget Survey by the Spanish Statistical Office, a demoeconomic model is applied to quantify the direct impacts, indirect impacts from interindustry links and induced impacts from income–consumption connections over a nine-year period (2006–2014). Then, the factors driving the evolution of total output, employment and value added during such period have been examined by using structural decomposition analysis.FindingsThe growing participation of consumption by pensioner households in final demand had proven crucial during the 2008 crisis to alleviate the negative trend in production and employment derived from the collapse in consumption suffered by the rest of households.Practical implicationsDetermining the underlying factors driving changes in both employment and income during the 2008 crisis can be of interest in political decision-making on the sustainability of the Spanish pension system.Social implicationsThe results of estimating both the employment and income supported by pensioners' consumption reveal the significant stabilizing effect of the public spending on pensions, particularly during the 2008 crisis.Originality/valueThe current Spanish approach of attaining the pension system sustainability by merely reducing social protection costs ignores the adverse consequences of a lower pensioners' demand. This paper addresses an alternative view in which pension spending is not considered a burden on economic growth but rather a means of improving the level of production and employment.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2019-0047

scholarly journals Evolution of knowledge on meniscal biomechanics: a 40 year perspective

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Amin Mohamadi ◽  
Kaveh Momenzadeh ◽  
Aidin Masoudi ◽  
Kempland C. Walley ◽  
Kenny Ierardi ◽  
...  
Keyword(s):  
Future Research ◽  
Fe Model ◽  
Cruciate Ligaments ◽  
Fe Modeling ◽  
Meniscal Tears ◽  
Medical Subject Headings ◽  
Model Studies ◽  
The Past ◽  
Mesh Terms ◽  
Kinematic Studies

Abstract Background Knowledge regarding the biomechanics of the meniscus has grown exponentially throughout the last four decades. Numerous studies have helped develop this knowledge, but these studies have varied widely in their approach to analyzing the meniscus. As one of the subcategories of mechanical phenomena Medical Subject Headings (MeSH) terms, mechanical stress was introduced in 1973. This study aims to provide an up-to-date chronological overview and highlights the evolutionary comprehension and understanding of meniscus biomechanics over the past forty years. Methods A literature review was conducted in April 2021 through PubMed. As a result, fifty-seven papers were chosen for this narrative review and divided into categories; Cadaveric, Finite element (FE) modeling, and Kinematic studies. Results Investigations in the 1970s and 1980s focused primarily on cadaveric biomechanics. These studies have generated the fundamental knowledge basis for the emergence of FE model studies in the 1990s. As FE model studies started to show comparable results to the gold standard cadaveric models in the 2000s, the need for understanding changes in tissue stress during various movements triggered the start of cadaveric and FE model studies on kinematics. Conclusion This study focuses on a chronological examination of studies on meniscus biomechanics in order to introduce concepts, theories, methods, and developments achieved over the past 40 years and also to identify the likely direction for future research. The biomechanics of intact meniscus and various types of meniscal tears has been broadly studied. Nevertheless, the biomechanics of meniscal tears, meniscectomy, or repairs in the knee with other concurrent problems such as torn cruciate ligaments or genu-valgum or genu-varum have not been extensively studied.

scholarly journals Newer Volatile Anesthetic Agents in Cardiac Anesthesia: Review of Literature

2021 ◽  
Author(s):  
Alka Mandke ◽  
Manjula Sarkar ◽  
Charulata Deshpande ◽  
Arun Maheshwari ◽  
Bhupesh Kumar ◽  
...  
Keyword(s):  
Volatile Anesthetic ◽  
Cochrane Library ◽  
Cochrane Central Register ◽  
Cardiac Anesthesia ◽  
Medical Subject Headings ◽  
Holistic View ◽  
Anesthetic Agents ◽  
Cardiac Anaesthesia ◽  
Mesh Terms ◽  
Inhalational Anaesthesia

AbstractMyocardial protection with volatile anesthetic agents have been suggested by multiple studies. These studies, however, are scattered and are often limited to a particular aspect of cardiac anesthesia. Older inhalational agents like halothane is known to cause significant hepatic damage in patients undergoing long duration surgeries while isoflurane is known to have marked vasodilating properties that also affects the coronary arteries leading to coronary “steal” phenomenon. Additionally, newer agents, like sevoflurane and desflurane, have shown more prominent cardioprotective effects than older agents. We searched ScholarOne, Medline, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library. The medical subject headings (MeSH) terms “anaesthesia, inhalational,” “anaesthesia, intravenous, or TIVA,” and “Cardiac anaesthesia or Cardiac Surgery” were used. Additional studies were identified by review of the reference sections of all eligible studies. The aim of this review article is to bring together the evidences with newer inhalational agents and provide a holistic view of their benefits and shortcomings in cardiac anesthesia.

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