scholarly journals Towards Identifying Author Confidence in Biomedical Articles

Data ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 18 ◽  
Author(s):  
Mihaela Onofrei Plămadă ◽  
Diana Trandabăț ◽  
Daniela Gîfu
Keyword(s):  
Medical Literature ◽  
Academic Research ◽  
Biomedical Text Mining ◽  
Huge Amount ◽  
Health Records ◽  
Effective Dissemination ◽  
First Impression ◽  
Series Of Experiments ◽  
Using Data ◽  
Open Archives

In an era where the volume of medical literature is increasing daily, researchers in the biomedical and clinical areas have joined efforts with language engineers to analyze the large amount of biomedical and molecular biology literature (such as PubMed), patient data, or health records. With such a huge amount of reports, evaluating their impact has long stopped being a trivial task. In this context, this paper intended to introduce a non-scientific factor that represents an important element in gaining acceptance of claims. We postulated that the confidence that an author has in expressing their work plays an important role in shaping the first impression that influences the reader’s perception of the paper. The results discussed in this paper were based on a series of experiments that were ran using data from the open archives initiative (OAI) corpus, which provides interoperability standards to facilitate effective dissemination of the content. This method may be useful to the direct beneficiaries (i.e., authors, who are engaged in medical or academic research), but also, to the researchers in the fields of biomedical text mining (BioNLP) and NLP, etc.

scholarly journals Towards identifying author confidence in biomedical articles

2018 ◽  
Author(s):  
Daniela Gifu ◽  
Mihaela Onofrei ◽  
Diana Trandabat
Keyword(s):  
Molecular Biology ◽  
Medical Literature ◽  
Academic Research ◽  
Patient Data ◽  
Huge Amount ◽  
Health Records ◽  
First Impression ◽  
Series Of Experiments ◽  
Open Archives ◽  
Open Archives Initiative

In an era when medical literature is increasing daily, researchers in biomedical and clinical areas have joined efforts with language engineers to analyze large amount of biomedical and molecular biology literature (such as PubMed), patient data or health records. With such a huge amount of reports, evaluating their impact has long seized to be a trivial task. In this context, this paper intends to introduce a non-scientific factor that represents an important element in the effort of gaining acceptance of claims. Thus, we postulate that the confidence the author is expressing in his work plays an important role in shaping the first impression that influences the reader’s perception of the paper. The results discussed in this paper are based on a series of experiments ran over data from the Open Archives Initiative (OAI) corpus that provides interoperability standards in order to facilitate the effectiveness dissemination of the content. This method can be useful to the direct beneficiaries (authors, who are engaged in medical or academic research), but, also, researchers in the fields of BioNLP and NLP, etc.

scholarly journals Association between triglycerides, known risk SNVs and conserved rare variation in SLC25A40 in a multi-ancestry cohort

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Elisabeth A. Rosenthal ◽  
David R. Crosslin ◽  
Adam S. Gordon ◽  
David S. Carrell ◽  
Ian B. Stanaway ◽  
...  
Keyword(s):  
Gene Cluster ◽  
Large Family ◽  
Missense Variant ◽  
Mixed Ancestry ◽  
Limited Sample ◽  
Health Records ◽  
Pathogenic Variants ◽  
Phenotype Data ◽  
Emerge Network ◽  
Using Data

Abstract Background Elevated triglycerides (TG) are associated with, and may be causal for, cardiovascular disease (CVD), and co-morbidities such as type II diabetes and metabolic syndrome. Pathogenic variants in APOA5 and APOC3 as well as risk SNVs in other genes [APOE (rs429358, rs7412), APOA1/C3/A4/A5 gene cluster (rs964184), INSR (rs7248104), CETP (rs7205804), GCKR (rs1260326)] have been shown to affect TG levels. Knowledge of genetic causes for elevated TG may lead to early intervention and targeted treatment for CVD. We previously identified linkage and association of a rare, highly conserved missense variant in SLC25A40, rs762174003, with hypertriglyceridemia (HTG) in a single large family, and replicated this association with rare, highly conserved missense variants in a European American and African American sample. Methods Here, we analyzed a longitudinal mixed-ancestry cohort (European, African and Asian ancestry, N = 8966) from the Electronic Medical Record and Genomics (eMERGE) Network. We tested associations between median TG and the genes of interest, using linear regression, adjusting for sex, median age, median BMI, and the first two principal components of ancestry. Results We replicated the association between TG and APOC3, APOA5, and risk variation at APOE, APOA1/C3/A4/A5 gene cluster, and GCKR. We failed to replicate the association between rare, highly conserved variation at SLC25A40 and TG, as well as for risk variation at INSR and CETP. Conclusions Analysis using data from electronic health records presents challenges that need to be overcome. Although large amounts of genotype data is becoming increasingly accessible, usable phenotype data can be challenging to obtain. We were able to replicate known, strong associations, but were unable to replicate moderate associations due to the limited sample size and missing drug information.

scholarly journals The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records (Preprint)

2019 ◽  
Author(s):  
Philip Held ◽  
Randy A Boley ◽  
Walter G Faig ◽  
John A O'Toole ◽  
Imran Desai ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Medical Center ◽  
Health Records ◽  
Clinical Notes ◽  
The Road ◽  
Clinical Encounters ◽  
Efficient Data ◽  
Data Points ◽  
Electronic Health ◽  
Using Data

UNSTRUCTURED Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

scholarly journals Closing the research-implementation gap using data science tools: a case study with pollinators of British Columbia

2020 ◽  
Author(s):  
Laura Melissa Guzman ◽  
Tyler Kelly ◽  
Lora Morandin ◽  
Leithen M’Gonigle ◽  
Elizabeth Elle
Keyword(s):  
British Columbia ◽  
Data Science ◽  
Academic Research ◽  
Science Methods ◽  
Research Implementation ◽  
Conservation Practice ◽  
Implementation Gap ◽  
Web App ◽  
Using Data

AbstractA challenge in conservation is the gap between knowledge generated by researchers and the information being used to inform conservation practice. This gap, widely known as the research-implementation gap, can limit the effectiveness of conservation practice. One way to address this is to design conservation tools that are easy for practitioners to use. Here, we implement data science methods to develop a tool to aid in conservation of pollinators in British Columbia. Specifically, in collaboration with Pollinator Partnership Canada, we jointly develop an interactive web app, the goal of which is two-fold: (i) to allow end users to easily find and interact with the data collected by researchers on pollinators in British Columbia (prior to development of this app, data were buried in supplements from individual research publications) and (ii) employ up to date statistical tools in order to analyse phenological coverage of a set of plants. Previously, these tools required high programming competency in order to access. Our app provides an example of one way that we can make the products of academic research more accessible to conservation practitioners. We also provide the source code to allow other developers to develop similar apps suitable for their data.

scholarly journals The reduction of Crosstalk in VLSI due to parallel bus structure using Data Compression Bus Encoding technique implemented on Artix 7 FPGA Architecture

2021 ◽  
Vol 9 (1) ◽  
pp. 456-460
Author(s):  
Syamala Yarlagadda, Srilakshmi Kaza, Anil chowdary Tummala, E Vijaya Babu, R. Prabhakar
Keyword(s):  
Power Consumption ◽  
Data Compression ◽  
Huge Amount ◽  
Significant Time ◽  
Planar Structures ◽  
Fpga Architecture ◽  
Bus Encoding ◽  
Bus Structure ◽  
Using Data ◽  
Encoding Method

In this work, a bus encoding method is proposed that reduces the effect of crosstalk. The crosstalk usually occurs when the data is in parallel communicated. In planar structures, the crosstalk effect is large due to the usage of parallel communication and wide data patterns. In bus technique, the huge amount of wires is laid in equal over a significant time. One way to reduce crosstalk without changing the parallel communicating data lines is to reduce the wideband data patterns so as to reduce the power utilization. The proposed encoding method can minimize the crosstalk by reducing wide data patterns without degrading the performance. The architecture is implemented on Artix 7 FPGA at a 28nm technology node. The simulation is done using the HDL tool and the results are compared with the existing FPGA architecture. With the proposed method, the wire density and the power consumption are reduced by 57.4% and 50% respectively as compared with existing 45 nm technologies.

Users' Guides to the Medical Literature series on social media (part 2): how to appraise studies using data from platforms

2021 ◽  
pp. bmjebm-2021-111850
Author(s):  
Ryan S D'Souza ◽  
Lubna Daraz ◽  
W Michael Hooten ◽  
Gordon Guyatt ◽  
Mohammad Hassan Murad
Keyword(s):  
Social Media ◽  
Medical Literature ◽  
Using Data

Knowledge Co production and Behavioural Change, Collaborative approaches for promoting low carbon mobility

2016 ◽  
Author(s):  
Stewart Barr ◽  
Gareth Shaw
Keyword(s):  
Climate Change ◽  
Behavioural Change ◽  
Academic Research ◽  
Low Carbon ◽  
Policy Makers ◽  
Productive Process ◽  
Emergent Literature ◽  
Using Data ◽  
The Uk ◽  
Personal Travel

Behavioural change has become regarded as a key tool for policy makers to promote behavioural change that can reduce carbon emissions from personal travel. Yet academic research has suggested that promoting low carbon travel behaviours, in particular those associated with leisure and tourism practices, is particularly challenging because of the highly valued and conspicuous nature of the consumption involved. Accordingly, traditional top-down approaches to developing behavioural change campaigns have largely been ineffectual in this field and this chapter explores innovative ways to understand and develop behavioural change campaigns that are driven from the bottom upwards. In doing so, we draw on emergent literature from management studies and social marketing to explore how ideas of service dominant logic can be used to engage consumers in developing each stage of a behavioural change campaign. Using data and insights from research conducted in the south-east of the UK, we outline and evaluate the process for co-producing knowledge about low carbon travel and climate change. We illustrate how behavioural change campaign creation can be an engaging, lively and productive process of knowledge and experience sharing. The chapter ends by considering the role that co-production and co-creation can have in developing strategies for low carbon mobility and, more broadly, the ways in which publics understand and react to anthropogenic climate change.

Examining the Implications of Process and Choice for Strategic Decision Making Effectiveness

2013 ◽  
pp. 344-359
Author(s):  
Paul L. Drnevich ◽  
Thomas H. Brush ◽  
Alok Chaturvedi
Keyword(s):  
Decision Making ◽  
Academic Research ◽  
Decision Processes ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Political Decision ◽  
Agent Based ◽  
Response Choice ◽  
Decision Making Processes ◽  
Using Data

Most strategic decision-making (SDM) approaches advocate the importance of decision-making processes and response choices for obtaining effective outcomes. Modern decision-making support system (DMSS) technology is often also needed for complex SDM, with recent research calling for more integrative DMSS approaches. However, scholars tend to take disintegrated approaches and disagree on whether rational or political decision-making processes result in more effective decision outcomes. In this study, the authors examine these issues by first exploring some of the competing theoretical arguments for the process-choice-effectiveness relationship, and then test these relationships empirically using data from a crisis response training exercise using an intelligent agent-based DMSS. In contrast to prior research, findings indicate that rational decision processes are not effective in crisis contexts, and that political decision processes may negatively influence both response choice and decision effectiveness. These results offer empirical evidence to confirm prior unsupported arguments that response choice is an important mediating factor between the decision-making process and its effectiveness. The authors conclude with a discussion of the implications of these findings and the application of agent-based simulation DMSS technologies for academic research and practice.

Efficiency Assessment of University-Industry Collaboration

2021 ◽  
pp. 155-175
Author(s):  
Ebru Yüksel Haliloğlu
Keyword(s):  
Industrial Development ◽  
Academic Research ◽  
Data Envelopment ◽  
Academic Knowledge ◽  
Technological Advances ◽  
Industry Collaboration ◽  
Close Cooperation ◽  
Using Data ◽  
New Applications ◽  
University Industry

Today, in addition to teaching and research roles, universities are one of major drivers of economic development and technological progress in society. To propagate technological innovation and industrial development, to implement output of academic research in practice universities should be in close cooperation with industry. University-industry collaborations have various benefits both for universities and industry. Universities gain additional funds for academic research, apply academic knowledge to industry; industry benefits from skilled human resources, new applications, and technological advances. Since university-industry collaborations have great mutual benefits for all partners, it is important to administer these operations effectively. Therefore, it is central to develop some efficiency indicators and efficiency measurement methods so that productive projects can be selected and funded more. This study aims to outline a framework on determinants of university-industry collaboration efficiency and construct a benchmark model to evaluate it using data envelopment analysis.

Sign in / Sign up

Export Citation Format

Share Document