Results 1 to 10 of about 13,643,641 (321)
Proceedings of the National Academy of Sciences, 2020 Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data ...
Yu, Bin, Kumbier, Karl
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Re-engineering Clinical Trial Management System Using Blockchain Technology
Blockchain in Healthcare Today, 2022 The annual ConV2X is a leading international health tech symposium driving real world evidence, strategy, research, operations and trends to create a blueprint for a new digital health era.
Yan Zhuang, PhD, National Institute of Health Data Science, Peking University +2 more
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Data Science — definition and structural representation
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2021 This article is a continuation of the discussion on the existing meanings and formalization of the definition of “Data Science” as an autonomous discipline, field of knowledge, clarification of its defining components, integration, and interaction ...
Pavlo Maslianko, Yevhenii Sielskyi
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Science and data science [PDF]
Proceedings of the National Academy of Sciences, 2017 Data science has attracted a lot of attention, promising to turn vast amounts of data into useful predictions and insights. In this article, we ask why scientists should care about data science. To answer, we discuss data science from three perspectives: statistical, computational, and human.
David M, Blei, Padhraic, Smyth
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Designing Data Science Workshops for Data-Intensive Environmental Science Research
Journal of Statistics and Data Science Education, 2021 Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs.
Allison S. Theobold +2 more
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IEEE Computer Graphics and Applications, 2017 Data science methods and approaches address all stages of transition from data to knowledge and action. Visualization of this data is essential for human understanding of the subject under study, analytical reasoning about it, and generating new knowledge.
Andrienko, Gennady +2 more
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Journal of the Medical Library Association, 2020 Increasingly, users of health and biomedical libraries need assistance with challenges they face in working with their own and others’ data. Librarians have a unique opportunity to provide valuable support and assistance in data science and open science ...
Lisa Federer +5 more
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