Browsing by Author "Börner, Katy"

Now showing 1 - 7 of 7
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    Just In Time: Challenges and Opportunities of First Aid Care Information Sharing for Supporting Epileptic Seizure Response
    (Association for Computing Machinery, 2021) Min, Aehong; Miller, Wendy; Rocha, Luis M.; Börner, Katy; Brattig Correia, Rion; Shih, Patrick C.; School of Nursing
    There are over three million people living with epilepsy in the U.S. People with epilepsy experience multiple daily challenges such as seizures, social isolation, social stigma, experience of physical and emotional symptoms, medication side effects, cognitive and memory deficits, care coordination difficulties, and risks of sudden unexpected death. In this work, we report findings collected from 3 focus groups of 11 people with epilepsy and caregivers and 10 follow-up questionnaires. We found that these participants feel that most people do not know how to deal with seizures. To improve others’ abilities to respond safely and appropriately to someone having seizures, people with epilepsy and caregivers would like to share and educate the public about their epilepsy conditions, reduce common misconceptions about seizures and prevent associated stigma, and get first aid help from the public when needed. Considering social stigma, we propose design implications of future technologies for effective delivery of appropriate first aid care information to bystanders around individuals with epilepsy when they experience a seizure.
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    Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer’s disease neuroimaging initiative
    (PLOS, 2017-11-02) Yao, Xiaohui; Yan, Jingwen; Ginda, Michael; Börner, Katy; Saykin, Andrew J.; Shen, Li; Radiology and Imaging Sciences, School of Medicine
    Background Alzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Methods Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. Results During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Conclusions Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.
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    Neurological Disorders and Publication Abstracts Follow Elements of Social Network Patterns when Indexed Using Ontology Tree-Based Key Term Search
    (Springer, 2014) Kulanthaivel, Anand; Light, Robert P.; Börner, Katy; Kong, Chin Hua; Jones, Josette F.; BioHealth Informatics, School of Informatics and Computing
    Disorders of the Central Nervous System (CNS) are worldwide causes of morbidity and mortality. In order to further investigate the nature of the CNS research, we generate from an initial reference a controlled vocabulary of CNS disorder-related terms and ontological tree structure for this vocabulary, and then apply the vocabulary in an analysis of the past ten years of abstracts (N = 10,488) from a major neuroscience journal. Using literal search methodology with our terminology tree, we find over 5,200 relationships between abstracts and clinical diagnostic topics. After generating a network graph of these document-topic relationships, we find that this network graph contains characteristics of document-author and other human social networks, including evidence of scale-free and power law-like node distributions. However, we also found qualitative evidence for Z-normal-type (albeit logarithmically skewed) distributions within disorder popularity. Lastly, we discuss potential consumer-centered as well as clinic-centered uses for our ontology and search methodology.
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    Open Data and Open Code for Big Science of Science Studies
    (2013) Light, Robert P.; Polley, David E.; Börner, Katy
    Historically, science of science studies were/are performed by single investigators or small teams. As the size and complexity of data sets and analyses scales up, a “Big Science” approach (Price, 1963) is required that exploits the expertise and resources of interdisciplinary teams spanning academic, government, and industry boundaries. Big science of science studies utilize “big data”, i.e., large, complex, diverse, longitudinal, and/or distributed datasets that might be owned by different stakeholders. They apply a systems science approach to uncover hidden patterns, bursts of activity, correlations, and laws. They make available open data and open code in support of replication of results, iterative refinement of approaches and tools, and education. This paper introduces a database-tool infrastructure that was designed to support big science of science studies. The open access Scholarly Database (SDB) (http://sdb.cns.iu.edu) provides easy access to 26 million paper, patent, grant, and clinical trial records. The open source Science of Science (Sci2) tool (http://sci2.cns.iu.edu) supports temporal, geospatial, topical, and network studies. The scalability of the infrastructure is examined. Results show that temporal analyses scale linearly with the number of records and file size, while the geospatial algorithm showed quadratic growth. The number of edges rather than nodes determined performance for network based algorithms.
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    Philanthro-metrics: Mining multi-million-dollar gifts
    (PLoS, 2017-05-26) Osili, Una O.; Ackerman, Jacqueline; Kong, Chin Hua; Light, Robert P.; Börner, Katy; Lilly Family School of Philanthropy
    The Million Dollar List (MDL, online at http://www.milliondollarlist.org) is a compilation of publicly announced charitable donations of $1 million or more from across the United States since 2000; as of December 2016, the database contains close to 80,000 gifts made by U.S. individuals, corporations, foundations, and other grant-making nonprofit organizations. This paper discusses the unique value of the Million Dollar List and provides unique insights to key questions such as: How does distance affect giving? How do networks impact million-dollar-plus gifts? Understanding the geospatial and temporal dimensions of philanthropy can assist researchers and policymakers to better understand the role of private funding in innovation and discovery. Moreover, the results from the paper emphasize the importance of philanthropy for fueling research and development in science, the arts, environment, and health. The paper also includes the limitations of the presented analyses and promising future work.
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    Topical, geospatial, and temporal diffusion of the 2015 North American Menopause Society position statement on nonhormonal management of vasomotor symptoms
    (Wolters Kluwer, 2017-10) Carpenter, Janet S.; Laine, Tei; Harrison, Blake; LePage, Meghan; Pierce, Taran; Hoteling, Nathan; Börner, Katy; School of Nursing
    OBJECTIVE: We sought to depict the topical, geospatial, and temporal diffusion of the 2015 North American Menopause Society position statement on the nonhormonal management of menopause-associated vasomotor symptoms released on September 21, 2015, and its associated press release from September 23, 2015. METHODS: Three data sources were used: online news articles, National Public Radio, and Twitter. For topical diffusion, we compared keywords and their frequencies among the position statement, press release, and online news articles. We also created a network figure depicting relationships across key content categories or nodes. For geospatial diffusion within the United States, we compared locations of the 109 National Public Radio (NPR) stations covering the statement to 775 NPR stations not covering the statement. For temporal diffusion, we normalized and segmented Twitter data into periods before and after the press release (September 12, 2015 to September 22, 2015 vs September 23, 2015 to October 3, 2015) and conducted a burst analysis to identify changes in tweets from before to after. RESULTS: Topical information diffused across sources was similar with the exception of the more scientific terms "vasomotor symptoms" or "vms" versus the more colloquial term "hot flashes." Online news articles indicated media coverage of the statement was mainly concentrated in the United States. NPR station data showed similar proportions of stations airing the story across the four census regions (Northeast, Midwest, south, west; P = 0.649). Release of the statement coincided with bursts in the menopause conversation on Twitter. CONCLUSIONS: The findings of this study may be useful for directing the development and dissemination of future North American Menopause Society position statements and/or press releases.
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    Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic
    (Sage, 2024) Qaurooni, Danial; Herr, Bruce W., II; Zappone, Sarah Renee; Wojciechowska, Klaudia; Börner, Katy; Schleyer, Titus; Medicine, School of Medicine
    The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard's usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard's use cases and limitations.