Literature-related discovery: common factors for Parkinson’s Disease and Crohn’s Disease

Kostoff, Ronald N.

doi:10.1007/s11192-014-1298-3

Cited by 21 publications

(25 citation statements)

References 64 publications

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“…In our case, one piece of knowledge would be the CORD‐19 and the other a set of articles on people with an ID. Especially, the cluster similarity technique (Fujita 2012) and bibliographical coupling technique (Kostoff 2014) seem to be suitable to construct new hypotheses on possible relations between corona viruses and people with an ID.…”

Section: Discussionmentioning

confidence: 99%

Coronaviruses and people with intellectual disability: an exploratory data analysis

Tummers

Çatal

Tobi³

et al. 2020

J intellect Disabil Res

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Background Corona virus disease 2019 (COVID‐19) has been announced as a new coronavirus disease by the World Health Organization. At the time of writing this article (April 2020), the world is drastically influenced by the COVID‐19. Recently, the COVID‐19 Open Research Dataset (CORD‐19) was published. For researchers on ID such as ourselves, it is of key interest to learn whether this open research dataset may be used to investigate the virus and its consequences for people with an ID. Methods From CORD‐19, we identified full‐text articles containing terms related to the ID care and applied a text mining technique, specifically the term frequency–inverse document frequency analysis in combination with K‐means clustering. Results Two hundred fifty‐nine articles contained one or more of our specified terms related to ID. We were able to cluster these articles related to ID into five clusters on different topics, namely: mental health, viral diseases, diagnoses and treatments, maternal care and paediatrics, and genetics. Conclusion The CORD‐19 open research dataset consists of valuable information about not only COVID‐19 disease but also ID and the relationship between them. We suggest researchers investigate literature‐based discovery approaches on the CORD‐19 and develop a new dataset that addresses the intersection of these two fields for further research.

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Section: Discussionmentioning

confidence: 99%

Coronaviruses and people with intellectual disability: an exploratory data analysis

Tummers

Çatal

Tobi³

et al. 2020

J intellect Disabil Res

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“…Kostoff and Schaller (2001), exploring the combination of qualitative and quantitative methodologies, aggregated TR variants into two fundamental TR approaches: expert-based and computer-based, and then, proposed a disruptive TR developing process which introduced the text mining component of Literature-Related Discovery (LRD) to identify technical disciplines and experts and assisted these experts in workshops (Kostoff et al 2004). Further, the LRD method (Kostoff et al 2008) has become an effective instrument to link two or more literature concepts that have heretofore not been linked, and is used to assist medical experts to explore potential treatments of quite a few diseases (Kostoff 2014;Kostoff and Patel 2015)., LRD does not link directly with TR development at this moment but it would be reasonable to imagine potential relationships.…”

Section: Hybrid Trmentioning

confidence: 99%

Technology roadmapping for competitive technical intelligence

Zhang

Robinson

Porter

et al. 2016

Technological Forecasting and Social Change

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International audienceUnderstanding the evolution and emergence of technology domains remains a challenge, particularly so for potentially breakthrough technologies. Though it is well recognized that emergence of new fields is complex and uncertain, to make decisions amidst such uncertainty, one needs to mobilize various sources of intelligence to identify known–knowns and known–unknowns to be able to choose appropriate strategies and policies. This competitive technical intelligence cannot rely on simple trend analyses because breakthrough technologies have little past to inform such trends, and positing the directions of evolution is challenging. Neither do qualitative tools, embracing the complexities, provide all the solutions, since transparent and repeatable techniques need to be employed to create best practices and evaluate the intelligence that comes from such exercises. In this paper, we present a hybrid roadmapping technique that draws on a number of approaches and integrates them into a multi-level approach (individual activities, industry evolutions and broader global changes) that can be applied to breakthrough technologies. We describe this approach in deeper detail through a case study on dye-sensitized solar cells. Our contribution to this special issue is to showcase the technique as part of a family of approaches that are emerging around the world to inform strategy and policy

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“…From the studies, gene–citation–gene (GCG) networks hit 96% coverage of BioGRID (Song et al, ) and are shown to be more dense and complex than entity–entity (GG) networks. For PD, Kostoff () attempted to discover potentially linked entities between two different papers through a bibliographic coupling‐based network.…”

Section: Related Workmentioning

confidence: 99%

Comparative evaluation of bibliometric content networks by tomographic content analysis: An application to Parkinson's disease

Lee

Kim

et al. 2016

Asso for Info Science & Tech

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To understand the current state of a discipline and to discover new knowledge of a certain theme, one builds bibliometric content networks based on the present knowledge entities. However, such networks can vary according to the collection of data sets relevant to the theme by querying knowledge entities. In this study we classify three different bibliometric content networks. The primary bibliometric network is based on knowledge entities relevant to a keyword of the theme, the secondary network is based on entities associated with the lower concepts of the keyword, and the tertiary network is based on entities influenced by the theme. To explore the content and properties of these networks, we propose a tomographic content analysis that takes a slice‐and‐dice approach to analyzing the networks. Our findings indicate that the primary network is best suited to understanding the current knowledge on a certain topic, whereas the secondary network is good at discovering new knowledge across fields associated with the topic, and the tertiary network is appropriate for outlining the current knowledge of the topic and relevant studies.

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Literature-related discovery: common factors for Parkinson’s Disease and Crohn’s Disease

Cited by 21 publications

References 64 publications

Coronaviruses and people with intellectual disability: an exploratory data analysis

Coronaviruses and people with intellectual disability: an exploratory data analysis

Technology roadmapping for competitive technical intelligence

Comparative evaluation of bibliometric content networks by tomographic content analysis: An application to Parkinson's disease

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