“…While disentangling the interrelationships that contribute to environmental exposures and their effects on human health over the course of life remains difficult, advances in data science and data sharing offer a path forward to explore data across disciplines to reveal new insights. …”
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“…Our method is able to show both short-term and long-term distribution of multiple important pollutants in the city, which demonstrates the potential and feasibility of dense monitoring data combined with advanced data science methods to support urban atmospheric environment fine-management, policy making, and public health studies.…”
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“…We envision digital twins as a solution combining clinical expertise with three prediction approaches: evidence-based medicine (clinical practice), data-driven models (data science) and mechanistic models (biomedical engineering). …”
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“…The tool suite is an example of data science techniques supporting data driven decision making within a military organization.…”
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“…Continual interdisciplinary developments in data science, biostatistics and epidemiology also motivated us to further discuss emerging topics in predictive and data‐driven (hypothesis‐less) analytics with machine learning. …”
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“…Results: The application of modern data science tools and practices allows analyses of data without the need for direct access – negating the need to send sensitive data. …”
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“…In addition, these newly solved structures motivated the emergence of huge data science and infrastructure efforts, which, together with advances in Deep Learning, have brought about a revolution in computational molecular biology. …”
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“…We recommend the use of Surgical Process Models and Surgical Data Science to incorporate the sequence of steps when teaching and assessing procedural skills.…”
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“…The integration of mental health research and ML data science will facilitate the transition to personalized and effective medicine, and, to do so, it is important that researchers from psychological/ medical disciplines/health care professionals and data scientists all share a common background and vision of the current research.…”
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“…APPROACH: The study will deploy a mobile app platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya. …”
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“…The challenge has been organized by the ATLAS collaboration associated to data scientists, in partnership with the Paris Saclay Center for Data Science, CERN and Google. The challenge ran from May to September 2014, drawing considerable attention. 1785 teams participated, making it the most popular challenge ever on the Kaggle platform. …”
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“…This book provides various ways to leverage data science to more intelligently and reliably to automate and manage a wireless network. …”
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“…The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. …”
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“…We propose a sampling-based customer acceptance approach that is fed with different combinations of these data to assess the impact of the current request on route efficiency and the ability to accept future requests. We propose a data-science process to investigate the best use of historical order data in terms of recency and amount of sampling data. …”
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“…Finally, we discuss the next version of the CBA APP, which incorporates an AI-driven component that reintegrates individual CBA projects using machine learning and other modern data science techniques. We argue that the APP, enhances CBA, development outcomes, and policy making efficiency for optimal prioritization of criminal justice resources. …”
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“…Precision agriculture, i.e., an (information technology)-enhanced approach to crop management, including a site-specific determination of agrochemicals, derives from the benefits of smart materials (SMs), data science, and nanosensors. Those typically feature fluorescent molecularly imprinted polymers or immunochemical aptamer artificial receptors integrated with electrochemical transducers. …”
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“…[Image: see text] Thermosets present sustainability challenges that could potentially be addressed through the design of deconstructable variants with tunable properties; however, the combinatorial space of possible thermoset molecular building blocks (e.g., monomers, cross-linkers, and additives) and manufacturing conditions is vast, and predictive knowledge for how combinations of these molecular components translate to bulk thermoset properties is lacking. Data science could overcome these problems, but computational methods are difficult to apply to multicomponent, amorphous, statistical copolymer materials for which little data exist. …”
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“…In response to this crisis, data science and machine learning (ML) offer crucial solutions to complex problems, including those posed by COVID-19. …”
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“…In the case of superconductors, the use of data science tools is to date slowed down by a lack of accessible data. …”
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