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  1. 1721
    “…Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. …”
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    A novel approach for standardizing clinical laboratory categorical test results using machine learning and string distance similarity
  2. 1722
    “…These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research.…”
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    openPDS: Protecting the Privacy of Metadata through SafeAnswers
  3. 1723
    “…These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. …”
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    GeNemo: a search engine for web-based functional genomic data
  4. 1724
    “…With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. …”
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    Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management
  5. 1725
    “…Summarizing, we were able to show that a novel toolbox comprising HPLC chromatogram fingerprinting and data science tools allowed the identification of E. coli lysis in a fast and reliable manner. …”
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    A novel toolbox for E. coli lysis monitoring
  6. 1726
    “…The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. …”
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    Best practice data life cycle approaches for the life sciences
  7. 1727
    “…The opportunities for development lie on a new forefront of innovation where medical physics integrates with engineering, data science, and modern computing capacities. Real-time DDMC is a systems integration challenge, and achieving it will require cooperation between hardware and software developers, and likely academia and industry. …”
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    Real-time data-driven motion correction in PET
  8. 1728
    “…These advances and applications have enabled: (1) the emergence of data science, which involves the development of new algorithms to analyze and visualize data; and (2) the use of engineering approaches to manipulate or create new biological organisms that have specific functions, such as production of industrial chemical precursors and development of environmental bio-based sensors. …”
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    National and Transnational Security Implications of Asymmetric Access to and Use of Biological Data
  9. 1729
    por Sur, Pragya, Candès, Emmanuel J.
    Publicado 2019
    “…Students in statistics or data science usually learn early on that when the sample size [Formula: see text] is large relative to the number of variables [Formula: see text] , fitting a logistic model by the method of maximum likelihood produces estimates that are consistent and that there are well-known formulas that quantify the variability of these estimates which are used for the purpose of statistical inference. …”
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    A modern maximum-likelihood theory for high-dimensional logistic regression
  10. 1730
    “…However, when working with people who are not experts in data science such as doctors, lawyers, and judges among others, finding interpretable algorithms can be a critical success factor. …”
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    The Univariate Flagging Algorithm (UFA): An interpretable approach for predictive modeling
  11. 1731
    “…The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. …”
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    ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data
  12. 1732
    “…To this end, we undertook the development of an innovative dissemination tool to implement fall-related evidence generated through state-of-the-art data science and information visualization approaches. …”
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    AN INNOVATIVE DATA-DRIVEN FALL PREVENTION COMMUNICATION TOOL FOR ADMINISTRATORS, NURSE MANAGERS, AND STAFF NURSES
  13. 1733
    “…The assessment of model skill, in turn, can benefit from modern data science approaches. Here we apply causal discovery algorithms to sea level pressure data from a large set of climate model simulations and, as a proxy for observations, meteorological reanalyses. …”
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    Causal networks for climate model evaluation and constrained projections
  14. 1734
    “…Simultaneously, there has been a convergence of scientific disciplines such as synthetic biology, data science, advanced computing and many other technologies, which all have applications in health. …”
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    Converging and emerging threats to health security
  15. 1735
    “…Together, there is unique capacity for clinical research, bioinformatics, data science, community engagement, regulatory science, institutional partnerships, training and career development, and other key translational elements. …”
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    Building capacity for collaborative research on opioid and other substance use disorders through the Clinical and Translational Science Award Program
  16. 1736
    “…OBJECTIVE: Science and technology sector constituting of data science, machine learning and artificial intelligence are contributing towards COVID-19. …”
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    A review of modern technologies for tackling COVID-19 pandemic
  17. 1737
    “…This study categorizes forecasting techniques into two types, namely, stochastic theory mathematical models and data science/machine learning techniques. Data collected from various platforms also play a vital role in forecasting. …”
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    Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art
  18. 1738
    “…Health Data Research UK (HDR UK) is the national Institute for Health Data Science, whose aim is to unite the UK’s health data to enable discoveries that improve people’s lives. …”
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    HDR UK supporting mobilising computable biomedical knowledge in the UK
  19. 1739
    “…Finally, we present an integrated review of analytical technologies and applications for monitoring plant growth, developed across disciplines, such as plant science, data science and sensors and Internet-of-things technologies, to improve plant productivity.…”
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    Decoding Plant–Environment Interactions That Influence Crop Agronomic Traits
  20. 1740
    por Ochoa, Xavier, Wise, Alyssa Friend
    Publicado 2020
    “…Learning analytics (the use of data science methods to generate actionable educational insights) have great potential to impact learning practices during the shift to digital. …”
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    Supporting the shift to digital with student-centered learning analytics
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