標(biāo)題: Titlebook: Big Data-Enabled Nursing; Education, Research Connie W. Delaney,Charlotte A. Weaver,Roy L. Simps Book 2017 Springer International Publishi [打印本頁(yè)] 作者: 日月等 時(shí)間: 2025-3-21 16:48
書(shū)目名稱(chēng)Big Data-Enabled Nursing影響因子(影響力)
作者: Obstreperous 時(shí)間: 2025-3-22 00:17
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.作者: Arthr- 時(shí)間: 2025-3-22 02:28 作者: 有毒 時(shí)間: 2025-3-22 04:42 作者: 兩棲動(dòng)物 時(shí)間: 2025-3-22 12:32
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.作者: incisive 時(shí)間: 2025-3-22 16:26 作者: 小官 時(shí)間: 2025-3-22 18:24 作者: Kernel 時(shí)間: 2025-3-22 21:22
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.作者: 為現(xiàn)場(chǎng) 時(shí)間: 2025-3-23 04:54 作者: 綠州 時(shí)間: 2025-3-23 07:18
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.作者: FLUSH 時(shí)間: 2025-3-23 11:53
1431-1917 xtualizes strategies for effective modern nursing practice.PHistorically, 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 an作者: ASSET 時(shí)間: 2025-3-23 16:19
Book 2017consequently 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 welco作者: Blemish 時(shí)間: 2025-3-23 19:13 作者: cringe 時(shí)間: 2025-3-23 23:47 作者: 不公開(kāi) 時(shí)間: 2025-3-24 05:22 作者: heart-murmur 時(shí)間: 2025-3-24 09:11
https://doi.org/10.1007/978-3-030-54271-9ne in which providers are accountable for quality, performance, and satisfaction. How can healthcare utilize the sea of data collected to optimize care for quality, performance, and satisfaction? One answer is to harness the power of that data and to manage the ability to perform meaningful analyses作者: gait-cycle 時(shí)間: 2025-3-24 14:30 作者: 暗指 時(shí)間: 2025-3-24 17:12 作者: 吝嗇性 時(shí)間: 2025-3-24 19:31
https://doi.org/10.1007/978-3-642-00485-8ices or mobile phone applications, the amount of health data is increasing in size, but also in speed and in complexity. “Big data” provides new opportunities for nurse clinicians and researchers to improve patient health, health services and patient safety. Following this unprecedented amount and c作者: RODE 時(shí)間: 2025-3-24 23:14
C.B. Dissanayake,Rohana Chandrajithgenerating that data, the National Innovation Network (NIN) for the National Center for Interprofessional Practice and Education (hereafter the National Center). We describe the raison d’être, characteristics, and ecosystem of the NIN-NCDR. The need for rigorously produced, scientifically sound evid作者: Lament 時(shí)間: 2025-3-25 06:15 作者: Measured 時(shí)間: 2025-3-25 11:17 作者: 生氣地 時(shí)間: 2025-3-25 11:42
Medical Issues in Italian Frescoes,e used for secondary research purposes. Many research collaboratives develop by building on past associations with one or two constituencies—typically academic institutions and integrated healthcare delivery systems. An emerging model is the academic/corporate model whose research partners include l作者: peritonitis 時(shí)間: 2025-3-25 16:31
Introduction to Medical Image Analysistential to affect the health of individual lives. The use of existing data provides fertile ground for healthcare professionals to conduct research that will maximize quality outcomes, develop algorithms of care to increase efficiency and safety, and create predictive models that have the ability to作者: BRUNT 時(shí)間: 2025-3-25 23:50
Introduction to Medio-Translatologyeed of improvement. Research—especially large clinical trials—is currently not only expensive, but also slow in both the setup and conduct of a study. Expanding the nation’s capacity to conduct clinical studies quickly and economically requires new infrastructure that takes advantage of data gathere作者: 浮夸 時(shí)間: 2025-3-26 00:32
Introduction to Medio-Translatologyrking capabilities, as well as the rise in wearable devices and consumer health care applications, have led to a considerable increase in the volume and variety of these data. While very large databases are being combined within electronic health records systems (EHRs), information reflecting nursin作者: bioavailability 時(shí)間: 2025-3-26 08:15
https://doi.org/10.1007/978-1-4613-3135-3ods and technologies. This chapter describes key methods that allow tackling hard discovery (analysis and modeling) questions with large datasets. Particular emphasis is placed on answering predictive and causal questions, coping with very large dimensionalities, and producing models that generalize作者: Lipoprotein 時(shí)間: 2025-3-26 08:57
Introduction to Metal Matrix Compositesr shift attention and is associated with poor patient outcomes. Managing these patients is a central nursing concern because patients with AMSC involve significant nursing resources and increased monitoring. Big Data can be used to develop cognitive support interventions at all levels, ranging from 作者: STING 時(shí)間: 2025-3-26 15:32
Big Data-Enabled Nursing978-3-319-53300-1Series ISSN 1431-1917 Series E-ISSN 2197-3741 作者: Consequence 時(shí)間: 2025-3-26 16:49
Connie W. Delaney,Charlotte A. Weaver,Roy L. SimpsDedicated 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作者: 他一致 時(shí)間: 2025-3-26 22:07
Health Informaticshttp://image.papertrans.cn/b/image/185735.jpg作者: 下垂 時(shí)間: 2025-3-27 04:15
https://doi.org/10.1007/978-3-319-53300-1Big Data; Healthcare Analytics; Medical databases; Electronic Health Record; EHR; Health system infrastru作者: 歌唱隊(duì) 時(shí)間: 2025-3-27 07:48
978-3-319-85120-4Springer International Publishing AG 2017作者: harbinger 時(shí)間: 2025-3-27 11:10 作者: BLAZE 時(shí)間: 2025-3-27 16:42
Big Data in Healthcare: A Wide Look at a Broad Subjectne in which providers are accountable for quality, performance, and satisfaction. How can healthcare utilize the sea of data collected to optimize care for quality, performance, and satisfaction? One answer is to harness the power of that data and to manage the ability to perform meaningful analyses作者: Pericarditis 時(shí)間: 2025-3-27 21:35
A Big Data Primer. Many organizations are using big data to improve their operations and/or create new products and services. Methods for generating data, how data is sensed, and then stored, in other words data collection, will be described. Mobile and internet technologies have transformed data collection for thes作者: opalescence 時(shí)間: 2025-3-27 23:25 作者: allergen 時(shí)間: 2025-3-28 04:41 作者: Femine 時(shí)間: 2025-3-28 09:39 作者: hazard 時(shí)間: 2025-3-28 13:22
Wrestling with Big Data: How Nurse Leaders Can Engageapproaches to “big data” is transformational and has the potential to dramatically improve the health and wellbeing of individuals on a national scale. However, although big data science offers great rewards, it has its challenges too. This is no more evident than in nursing where the sheer amount o作者: Gustatory 時(shí)間: 2025-3-28 17:47
Inclusion of Flowsheets from Electronic Health Records to Extend Data for Clinical and Translationaled by nursing and other healthcare professionals. Standardization of the data, however, is required for it to be useful for big data science. In this chapter, an example of one CDR funded by NIH’s CTSA demonstrates how flowsheet data can add data repositories for big data science. A specific example作者: degradation 時(shí)間: 2025-3-28 19:21
Working in the New Big Data World: Academic/Corporate Partnership Modele used for secondary research purposes. Many research collaboratives develop by building on past associations with one or two constituencies—typically academic institutions and integrated healthcare delivery systems. An emerging model is the academic/corporate model whose research partners include l作者: 尖叫 時(shí)間: 2025-3-29 01:15 作者: 人類(lèi)學(xué)家 時(shí)間: 2025-3-29 05:40
Answering Research Questions with National Clinical Research Networkseed of improvement. Research—especially large clinical trials—is currently not only expensive, but also slow in both the setup and conduct of a study. Expanding the nation’s capacity to conduct clinical studies quickly and economically requires new infrastructure that takes advantage of data gathere作者: CRACY 時(shí)間: 2025-3-29 10:56 作者: 擔(dān)心 時(shí)間: 2025-3-29 11:39
State of the Science in Big Data Analyticsods and technologies. This chapter describes key methods that allow tackling hard discovery (analysis and modeling) questions with large datasets. Particular emphasis is placed on answering predictive and causal questions, coping with very large dimensionalities, and producing models that generalize作者: Cardioversion 時(shí)間: 2025-3-29 18:53
Big Data Analytics Using the VA’s ‘VINCI’ Database to Look at Deliriumr shift attention and is associated with poor patient outcomes. Managing these patients is a central nursing concern because patients with AMSC involve significant nursing resources and increased monitoring. Big Data can be used to develop cognitive support interventions at all levels, ranging from 作者: ANNUL 時(shí)間: 2025-3-29 20:13 作者: RODE 時(shí)間: 2025-3-30 01:44
Big Data in Healthcare: A Wide Look at a Broad Subjectnts are passing this data to their care providers for inclusion in care decision-making. Data is coming from external care providers in disparate systems and is passed from one provider to another as patients traverse a trajectory of care that may or may not be seamless. At each juncture, the data i作者: 大氣層 時(shí)間: 2025-3-30 06:42 作者: Analogy 時(shí)間: 2025-3-30 09:45 作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-30 13:08 作者: 地名表 時(shí)間: 2025-3-30 18:29
