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Titlebook: Big Data-Enabled Nursing; Education, Research Connie W. Delaney,Charlotte A. Weaver,Roy L. Simps Book 2017 Springer International Publishi

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发表于 2025-3-21 16:48:14 | 显示全部楼层 |阅读模式
期刊全称Big Data-Enabled Nursing
期刊简称Education, Research
影响因子2023Connie W. Delaney,Charlotte A. Weaver,Roy L. Simps
视频video
发行地址Dedicated to teaching the application of big data within nursing.Makes extensive use of illustrations to expand on key thematic points.Contextualizes strategies for effective modern nursing practice.P
学科分类Health Informatics
图书封面Titlebook: Big Data-Enabled Nursing; Education, Research  Connie W. Delaney,Charlotte A. Weaver,Roy L. Simps Book 2017 Springer International Publishi
影响因子Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing.  It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled b
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发表于 2025-3-22 00:17:40 | 显示全部楼层
Medical Issues in Italian Frescoes,m and patient conditions and states can be achieved. Additional efforts by national workgroups to create information models from flowsheets and standardize assessment terms are described to support big data science.
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A Big Data Primerowns the data, the products generated from the data, and applications of the data? Challenges and tools for data analytics and data visualization of big data will be described, thus, setting the foundation for the rest of the book.
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State of the Science in Big Data Analyticso addressed, such as robust protocols for model selection and error estimation, analysis of unstructured data, analysis of multimodal data, network science approaches, deep learning, active learning, and other methods. The chapter concludes with a discussion of several open and challenging areas.
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Wrestling with Big Data: How Nurse Leaders Can Engagend business intelligence reports are just a few of the many data requirements nurse leaders encounter daily. This chapter describes the challenges nurse leaders face today and discusses strategies that nurse leaders can use to leverage big data to meet the Triple Aim of improving quality, improving the patient experience while reducing cost.
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