Extracting and modeling geographic information from scientific articles

Scientific articles often contain relevant geographic information such as where field work was performed or where patients were treated. Most often, this information appears in the full-text article contents as a description in natural language including place names, with no accompanying machine-readable geographic metadata. Automatically extracting this geographic information could help conduct meta-analyses, find geographical research gaps, and retrieve articles using spatial search criteria. Research on this problem is still in its infancy, with many works manually processing corpora for locations and few cross-domain studies. In this paper, we develop a fully automatic pipeline to extract and represent relevant locations from scientific articles, applying it to two varied corpora. We obtain good performance, with full pipeline precision of 0.84 for an environmental corpus, and 0.78 for a biomedical corpus. Our results can be visualized as simple global maps, allowing human annotators to both explore corpus patterns in space and triage results for downstream analysis. Future work should not only focus on improving individual pipeline components, but also be informed by user needs derived from the potential spatial analysis and exploration of such corpora.

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Geographic information - Cross-domain vocabularies

10.3403/30348202 ◽

2018 ◽

Keyword(s):

Geographic Information ◽

Cross Domain

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Sleep and cognition

10.1093/oso/9780198778240.003.0004 ◽

2018 ◽

Author(s):

Donald L. Bliwise ◽

Michael K. Scullin

Keyword(s):

Cognitive Function ◽

Natural History ◽

Population Health ◽

Effect Sizes ◽

Biological Plausibility ◽

Vast Array ◽

Neurobiological Substrates ◽

Meta Analyses ◽

Sleep And Cognition ◽

Future Work

Possible associations between sleep and cognition are provocative across different domains and hold the promise of prevention or reversibility. A vast array of studies has been reported. Evidence is suggestive but hardly definitive. We provide an overview of this literature, adopting the framework of Hill’s perspective on epidemiological causation. With rare exception, formal meta-analyses have yet to appear. Apparent consistency of findings suggests relationships, but the diversity of findings involving specific components of cognitive function raises interpretative caution. Large effect sizes have been noted, but small-to-moderate effects predominate. Natural history data are similarly enticing, and studies of biological plausibility and gradient indicate likely neurobiological substrates. Perhaps the ultimate population-health criterion, demonstration of reversibility of impairment, remains elusive at best. This area offers an exciting topic for future work.

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The use of chatbots as supportive agents for people seeking help for drug and alcohol addiction: A systematic review. (Preprint)

10.2196/preprints.31227 ◽

2021 ◽

Author(s):

Lisa Ogilvie ◽

Jerome Carson ◽

Julie Prescott

Keyword(s):

Mixed Methods ◽

Healthcare Setting ◽

The Body ◽

Alcohol Addiction ◽

Bibliographic Databases ◽

Ethical Implications ◽

Qualitative Work ◽

Meta Analyses ◽

Future Work ◽

Drug And Alcohol

BACKGROUND The use of chatbots in healthcare is an area of study receiving increased academic interest. As the knowledge base grows, the granularity in the level of research is being refined, seeing more targeted work in specific areas of healthcare, for example, chatbots for anxiety and depression, cancer care, and pregnancy support. This paper focuses on the targeted application of chatbots in drug and alcohol addiction. OBJECTIVE The aim of this paper is to systematically review and summarise the research conducted on the use of chatbots in the field of addiction, specifically the use of chatbots as supportive agents for those who suffer from drug and alcohol addiction. METHODS A systematic search of bibliographic databases using the broad search criteria of “chatbot and addiction,” identified papers for screening. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the Mixed Methods Appraisal Tool were used, which resulted in the quality assessment and review of 5 papers. RESULTS Although the body of research in this field is limited, what has been published shows promising results. A combination of quantitative, qualitative, and mixed methods studies were reviewed, among which statistically significant findings were reported on the efficacy of chatbots targeted at drug and alcohol addiction. These findings were also substantiated in the qualitative work reviewed. A strong message of caution was conveyed however on the ethical implications of using chatbots to afford support to addicted individuals. CONCLUSIONS The literature reviewed shows that more work is needed to appreciate solutions that leverage existing data, such as big data available from social media, or that which is accessed by prevalent market leading chatbots. It also highlighted ethical concerns over the use of a non-human agent to afford support to those with drug and alcohol addiction. It was reported however, that statistically significant results were returned for ‘bespoke’ chatbots in this area of healthcare, setting a promising foundation for future work.

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Design of cooperative update mechanism of national geographic conditions monitoring and basic surveying and mapping

Abstracts of the ICA ◽

10.5194/ica-abs-1-231-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-2

Author(s):

Fujun Luo ◽

Yousong Zhao

Keyword(s):

Image Interpretation ◽

Field Work ◽

Geographic Information ◽

National Geographic ◽

Internal Work ◽

Field Verification ◽

Collection Data ◽

Geographical Elements ◽

The One ◽

Surveying And Mapping

Abstract. National geographic conditions monitoring and basic surveying and mapping are two important tasks of the surveying and mapping department, and they are similar in production organization and technology realization. In the process of operation, both of them need to carry out internal collection, base map production, field verification and so on. It is operationally feasible to carry out cooperative production of national geographic conditions monitoring and basic surveying and mapping. From the perspective of technical process and method, both of them are carried out by combination internal and field work. Firstly, based on remote sensing images and thematic geographic data, the internal work will perform image interpretation and obtain staged results data. Then, the field verification will be carried out to make judgments and adjustments. Finally, the results of the field verification will be transferred back to the internal work, and the data will be further edited and organized in the internal work to obtain the final data.Basic surveying and mapping focuses on abstract representation of the real world, but lacks comprehensive integration of information and in-depth knowledge mining. National geographic condition monitoring focuses on the spatial distribution, characteristics and interrelations of natural and human geographical elements on the surface. There are many differences between basic surveying and mapping and national geographic conditions monitoring in the content and index of data collection, data stratification and element attribute. But basic surveying and mapping results are the basic data for national geographic conditions monitoring and national geographic conditions monitoring data is an important update data source for basic surveying and mapping.On the one hand, part of the geographic information can be updated on the basis of extracting relevant basic geographic information element data and attribute information, On the other hand, timely basic geographic information data can be used as the direct basis for the collection of geographic information.This paper designs the technical methods and workflow of the cooperative update mechanism based on the relevant technical documents of national geographic conditions monitoring and basic surveying and mapping. It will enable one-time acquisition of data needed for the national geographic conditions monitoring and basic surveying and mapping, "one-time collection, classification and utilization". It will save a lot of time and effort, reduce workload and improve productivity.

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Improving Transparency, Falsifiability, and Rigour by Making Hypothesis Tests Machine Readable

10.31234/osf.io/5xcda ◽

2020 ◽

Cited By ~ 2

Author(s):

Daniel Lakens ◽

Lisa Marie DeBruine

Keyword(s):

Peer Review ◽

Hypothesis Test ◽

Scientific Information ◽

Real Life ◽

R Package ◽

Statistical Prediction ◽

Hypothesis Tests ◽

Research Questions ◽

Meta Analyses ◽

Machine Readable

Making scientific information machine-readable greatly facilitates its re-use. Many scientific articles have the goal to test a hypothesis, so making the tests of statistical predictions easier to find and access could be very beneficial. We propose an approach that can be used to make hypothesis tests machine readable. We believe there are two benefits to specifying a hypothesis test in a way that a computer can evaluate whether the statistical prediction is corroborated or not. First, hypothesis test will become more transparent, falsifiable, and rigorous. Second, scientists will benefit if information related to hypothesis tests in scientific articles is easily findable and re-usable, for example when performing meta-analyses, during peer review, and when examining meta-scientific research questions. We examine what a machine readable hypothesis test should look like, and demonstrate the feasibility of machine readable hypothesis tests in a real-life example using the fully operational prototype R package scienceverse.

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Geographic Information Retrieval: Progress and Challenges in Spatial Search of Text

Foundations and Trends® in Information Retrieval ◽

10.1561/1500000034 ◽

2018 ◽

Vol 12 (2-3) ◽

pp. 164-318 ◽

Cited By ~ 25

Author(s):

Ross S. Purves ◽

Paul Clough ◽

Christopher B. Jones ◽

Mark H. Hall ◽

Vanessa Murdock

Keyword(s):

Information Retrieval ◽

Geographic Information ◽

Geographic Information Retrieval ◽

Spatial Search

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An Applicative Survey on Few-Shot Learning

Recent Patents on Engineering ◽

10.2174/1872212115666210715121344 ◽

2021 ◽

Vol 15 ◽

Author(s):

Jianwei Zhang ◽

Xubin Zhang ◽

Lei Lv ◽

Yining Di ◽

Wei Chen

Keyword(s):

Large Scale ◽

Representation Learning ◽

Language Models ◽

Data Sets ◽

Research Directions ◽

Large Scale Data ◽

Cross Domain ◽

Meta Learning ◽

Definition Of ◽

Future Work

Background: Learning discriminative representation from large-scale data sets has made a breakthrough in decades. However, it is still a thorny problem to generate representative embedding from limited examples, for example, a class containing only one image. Recently, deep learning-based Few-Shot Learning (FSL) has been proposed. It tackles this problem by leveraging prior knowledge in various ways. Objective: In this work, we review recent advances of FSL from the perspective of high-dimensional representation learning. The results of the analysis can provide insights and directions for future work. Methods: We first present the definition of general FSL. Then we propose a general framework for the FSL problem and give the taxonomy under the framework. We survey two FSL directions: learning policy and meta-learning. Results: We review the advanced applications of FSL, including image classification, object detection, image segmentation and other tasks etc., as well as the corresponding benchmarks to provide an overview of recent progress. Conclusion: FSL needs to be further studied in medical images, language models, and reinforcement learning in future work. In addition, cross-domain FSL, successive FSL, and associated FSL are more challenging and valuable research directions.

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Towards developing a consensus assessment framework for global emergency medicine fellowships

BMC Emergency Medicine ◽

10.1186/s12873-019-0286-6 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Haiko Kurt Jahn ◽

James Kwan ◽

Gerard O’Reilly ◽

Heike Geduld ◽

Katherine Douglass ◽

...

Keyword(s):

Emergency Medicine ◽

Working Group ◽

Field Work ◽

Fellowship Training ◽

Assessment Tools ◽

Standardized Assessments ◽

Main Body ◽

Validity And Reliability ◽

Fellowship Programs ◽

Future Work

Abstract Background The number of Global Emergency Medicine (GEM) Fellowship training programs are increasing worldwide. Despite the increasing number of GEM fellowships, there is not an agreed upon approach for assessment of GEM trainees. Main body In order to study the lack of standardized assessment in GEM fellowship training, a working group was established between the International EM Fellowship Consortium (IEMFC) and the International Federation for Emergency Medicine (IFEM). A needs assessment survey of IEMFC members and a review were undertaken to identify assessment tools currently in use by GEM fellowship programs; what relevant frameworks exist; and common elements used by programs with a wide diversity of emphases. A consensus framework was developed through iterative working group discussions. Thirty-two of 40 GEM fellowships responded (80% response). There is variability in the use and format of formal assessment between programs. Thirty programs reported training GEM fellows in the last 3 years (94%). Eighteen (56%) reported only informal assessments of trainees. Twenty-seven (84%) reported regular meetings for assessment of trainees. Eleven (34%) reported use of a structured assessment of any sort for GEM fellows and, of these, only 2 (18%) used validated instruments modified from general EM residency assessment tools. Only 3 (27%) programs reported incorporation of formal written feedback from partners in other countries. Using these results along with a review of the available assessment tools in GEM the working group developed a set of principles to guide GEM fellowship assessments along with a sample assessment for use by GEM fellowship programs seeking to create their own customized assessments. Conclusion There are currently no widely used assessment frameworks for GEM fellowship training. The working group made recommendations for developing standardized assessments aligned with competencies defined by the programs, that characterize goals and objectives of training, and document progress of trainees towards achieving those goals. Frameworks used should include perspectives of multiple stakeholders including partners in other countries where trainees conduct field work. Future work may evaluate the usability, validity and reliability of assessment frameworks in GEM fellowship training.

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Collaborative Mapping and GIS

Handbook of Research on Geoinformatics ◽

10.4018/978-1-59140-995-3.ch045 ◽

2010 ◽

pp. 388-399 ◽

Cited By ~ 1

Author(s):

Edward Mac Gillavry

Keyword(s):

Web Services ◽

Mobile Devices ◽

Real World ◽

Information Infrastructure ◽

Geographic Information ◽

Web Technologies ◽

Location Aware ◽

Collaborative Mapping ◽

Machine Readable ◽

Complementary And Alternative

The collection and dissemination of geographic information has long been the prerogative of national mapping agencies. Nowadays, location-aware mobile devices could potentially turn everyone into a mapmaker. Collaborative mapping is an initiative to collectively produce models of real-world locations online that people can then access and use to virtually annotate locations in space. This chapter describes the technical and social developments that underpin this revolution in mapmaking. It presents a framework for an alternative geographic information infrastructure that draws from collaborative mapping initiatives and builds on established Web technologies. Storing geographic information in machine-readable formats and exchanging geographic information through Web services, collaborative mapping may enable the “napsterisation” of geographic information, thus providing complementary and alternative geographic information from the products created by national mapping agencies.

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Instrumented Analysis of the Sit-to-Stand Movement for Geriatric Screening: A Systematic Review

Bioengineering ◽

10.3390/bioengineering7040139 ◽

2020 ◽

Vol 7 (4) ◽

pp. 139

Author(s):

Brajesh Shukla ◽

Jennifer Bassement ◽

Vivek Vijay ◽

Sandeep Yadav ◽

David Hewson

Keyword(s):

Systematic Review ◽

At Risk ◽

Older People ◽

Search Strategy ◽

Risk Of Falling ◽

Sit To Stand ◽

Risk Of Falls ◽

Geriatric Screening ◽

Meta Analyses ◽

Future Work

The Sit-to-Stand (STS) is a widely used test of physical function to screen older people at risk of falls and frailty and is also one of the most important components of standard screening for sarcopenia. There have been many recent studies in which instrumented versions of the STS (iSTS) have been developed to provide additional parameters that could improve the accuracy of the STS test. This systematic review aimed to identify whether an iSTS is a viable alternative to a standard STS to identify older people at risk of falling, frailty, and sarcopenia. A total of 856 articles were found using the search strategy developed, with 12 articles retained in the review after screening based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Six studies evaluated the iSTS in fallers, five studies in frailty and only one study in both fallers and frailty. The results showed that power and velocity parameters extracted from an iSTS have the potential to improve the accuracy of screening when compared to a standard STS. Future work should focus on standardizing the segmentation of the STS into phases to enable comparison between studies and to develop devices integrated into the chair used for the test to improve usability.

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