“…Our approach, ‘Multiscale Graph Correlation’ (MGC), is a dependence test that juxtaposes disparate data science techniques, including k-nearest neighbors, kernel methods, and multiscale analysis. …”
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“…The National Institute of Standards and Technology data science evaluation plant identification challenge is a new periodic competition focused on improving and generalizing remote sensing processing methods for forest landscapes. …”
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“…Major advances in concrete understanding of disease etiology have been driven by a willingness to learn about and incorporate into epidemiology developments in biology and cognate data science disciplines. If fundamental epidemiologic principles regarding the rooting of disease risk within populations are retained, recent methodological developments combined with increased biological understanding and data sciences capability should herald a fruitful post–Modern Epidemiology world.…”
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“…Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. …”
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“…This dataset can attract the attention of researchers related to different fields on knowledge, such as data science, social science, network science, health informatics, tourism, infodemiology, and others.…”
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“…The results of this task provide significant insights about potentially highly valuable tabular data, as recent works have shown, enabling a new family of data analytics and data science applications. Despite significant amount of work on various flavors of this problem, there is a lack of a common framework to conduct a systematic evaluation of state-of-the-art systems. …”
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“…The rapid proliferation of sensors and big data repositories offer many new opportunities for data science. Among many application domains, the analysis of large trajectory datasets generated from people’s movements at the city scale is one of the most promising research avenues still to explore. …”
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“…This access provides an unprecedented opportunity for data science technologies to derive data-driven insights and improve the quality of care delivery. …”
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“…This exploratory work highlights the potential of a set of new technologies, freely available, for the construction of low cost data science tools that have high social impact. At the same time, it discusses and seeks to suggest practical solutions for the complex and serious problem of illegal mining and the proliferation of tailings dams, which pose high risks to the population and the environment, especially in developing countries.…”
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“…Newly funded Centers focus on interventions to promote caregiving mastery, integrate the use of technology in care support to improve assessments and interventions in care provision, develop behavioral interventions to reduce isolation and promote social connectedness in caregivers, promote health in racial/ethnic minorities, and apply insights from data science and behavioral economics to improve palliative care delivery and long-term support facilities for persons with dementia and their caregivers. …”
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“…We expect that these frontiers, enabled by the ongoing revolution of big data science, will drive forward more advanced and powerful strain engineering strategies.…”
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“…With the advancement in data science tools and increasing computational capacities, we can use bibliometric data for calculating a researcher's mobility on location and a disciplinary focus over time. …”
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“…However, efforts toward integration of MMM data, advancements in data science, and the availability of cloud-based infrastructures are now affording the opportunity for MMM to advance the care of patients with brain trauma. …”
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“…Outlining the idea of ethics built on the foundations of relationality, this paper calls for a rethinking of justice and ethics as a set of broad, contingent, and fluid concepts and down-to-earth practices that are best viewed as a habit and not a mere methodology for data science. As such, this paper mainly offers critical examinations and reflection and not “solutions.”…”
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“…With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. …”
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“…The use of data science tools to provide the emergence of non-trivial chemical features for catalyst design is an important goal in catalysis science. …”
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“…On the other end, Science and technology sector constituting of data science, machine learning, rapid diagnostic tests, mobile-first telehealth and computational simulation systems for drug development, artificial intelligence, virtual collaboration, and data tracking are complex ways of using the technology that have strengthened our pandemic response.…”
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“…Ben Glocker (an expert in machine learning for medical imaging, Imperial College London), Mirco Musolesi (a data science and digital health expert, University College London), Jonathan Richens (an expert in diagnostic machine learning models, Babylon Health) and Caroline Uhler (a computational biology expert, MIT) talked to Nature Communications about their research interests in causality inference and how this can provide a robust framework for digital medicine studies and their implementation, across different fields of application.…”
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“…This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.…”
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