Literature DB >> 27918361

Big Data: Contributions, Limitations, and Implications for Cardiovascular Nurses.

Kelly T Gleason1, Cheryl R Dennison Himmelfarb.   

Abstract

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Year:  2017        PMID： 27918361      PMCID： PMC5393269          DOI： 10.1097/JCN.0000000000000384

Source DB:  PubMed          Journal:  J Cardiovasc Nurs        ISSN： 0889-4655            Impact factor:   2.083


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  11 in total

1.  The Promise and Potential Perils of Big Data for Advancing Symptom Management Research in Populations at Risk for Health Disparities.

Authors:  Suzanne Bakken; Nancy Reame
Journal:  Annu Rev Nurs Res       Date:  2016

2.  Effect of race on outcomes (stroke and death) in patients >65 years with atrial fibrillation.

Authors:  Rajesh Kabra; Peter Cram; Saket Girotra; Mary Vaughan Sarrazin
Journal:  Am J Cardiol       Date:  2015-04-16       Impact factor: 2.778

3.  Big data: the management revolution.

Authors:  Andrew McAfee; Erik Brynjolfsson
Journal:  Harv Bus Rev       Date:  2012-10

Review 4.  Big data analytics to improve cardiovascular care: promise and challenges.

Authors:  John S Rumsfeld; Karen E Joynt; Thomas M Maddox
Journal:  Nat Rev Cardiol       Date:  2016-03-24       Impact factor: 32.419

5.  Standardizing Physiologic Assessment Data to Enable Big Data Analytics.

Authors:  Susan A Matney; Theresa Tess Settergren; Jane M Carrington; Rachel L Richesson; Amy Sheide; Bonnie L Westra
Journal:  West J Nurs Res       Date:  2016-07-21       Impact factor: 1.967

6.  From Value Assessment to Value Cocreation: Informing Clinical Decision-Making with Medical Claims Data.

Authors:  Steven Thompson; Stephen Varvel; Maciek Sasinowski; James P Burke
Journal:  Big Data       Date:  2016-09       Impact factor: 2.128

7.  Association Between Atrial Fibrillation Symptoms, Quality of Life, and Patient Outcomes: Results From the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF).

Authors:  James V Freeman; DaJuanicia N Simon; Alan S Go; John Spertus; Gregg C Fonarow; Bernard J Gersh; Elaine M Hylek; Peter R Kowey; Kenneth W Mahaffey; Laine E Thomas; Paul Chang; Eric D Peterson; Jonathan P Piccini
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2015-06-09

8.  DATA MINING APPROACH FOR IN-HOSPITAL TREATMENT OUTCOME IN PATIENTS WITH ACUTE CORONARY SYNDROME.

Authors:  Miroslava Sladojević; Milenko Čanković; Snežana Čemerlić; Bojan Mihajlović; Filip Ađić; Milana Jaraković
Journal:  Med Pregl       Date:  2015 May-Jun

9.  The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

Authors:  Ronald Margolis; Leslie Derr; Michelle Dunn; Michael Huerta; Jennie Larkin; Jerry Sheehan; Mark Guyer; Eric D Green
Journal:  J Am Med Inform Assoc       Date:  2014-07-09       Impact factor: 4.497

Review 10.  Big data analytics in healthcare: promise and potential.

Authors:  Wullianallur Raghupathi; Viju Raghupathi
Journal:  Health Inf Sci Syst       Date:  2014-02-07
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  2 in total

1.  Identifying Targets to Improve Heart Failure Outcomes for Patients Receiving Home Healthcare Services: The Relationship of Functional Status and Pain.

Authors:  Youjeong Kang; Xiaoming Sheng; Josef Stehlik; Kathi Mooney
Journal:  Home Healthc Now       Date:  2020 Jan/Feb

2.  A data mining based clinical decision support system for survival in lung cancer.

Authors:  Beatriz Pontes; Francisco Núñez; Cristina Rubio; Alberto Moreno; Isabel Nepomuceno; Jesús Moreno; Jon Cacicedo; Juan Manuel Praena-Fernandez; German Antonio Escobar Rodriguez; Carlos Parra; Blas David Delgado León; Eleonor Rivin Del Campo; Felipe Couñago; Jose Riquelme; Jose Luis Lopez Guerra
Journal:  Rep Pract Oncol Radiother       Date:  2021-12-30
  2 in total

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