Literature DB >> 15520581

Data mining as a tool for research and knowledge development in nursing.

Anne M Berger1, Charles R Berger.   

Abstract

The ability to collect and store data has grown at a dramatic rate in all disciplines over the past two decades. Healthcare has been no exception. The shift toward evidence-based practice and outcomes research presents significant opportunities and challenges to extract meaningful information from massive amounts of clinical data to transform it into the best available knowledge to guide nursing practice. Data mining, a step in the process of Knowledge Discovery in Databases, is a method of unearthing information from large data sets. Built upon statistical analysis, artificial intelligence, and machine learning technologies, data mining can analyze massive amounts of data and provide useful and interesting information about patterns and relationships that exist within the data that might otherwise be missed. As domain experts, nurse researchers are in ideal positions to use this proven technology to transform the information that is available in existing data repositories into useful and understandable knowledge to guide nursing practice and for active interdisciplinary collaboration and research.

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Year:  2004        PMID: 15520581     DOI: 10.1097/00024665-200405000-00006

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  7 in total

1.  Predicting the likelihood of falls among the elderly using likelihood basis pursuit technique.

Authors:  Kanittha Volrathongchai; Patricia F Brennan; Michael C Ferris
Journal:  AMIA Annu Symp Proc       Date:  2005

2.  Extracting nursing practice patterns from structured labor and delivery data sets.

Authors:  Eric S Hall; Sidney N Thornton
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

3.  Building a computer program to support children, parents, and distraction during healthcare procedures.

Authors:  Kirsten Hanrahan; Ann Marie McCarthy; Charmaine Kleiber; Kaan Ataman; W Nick Street; M Bridget Zimmerman; Anne L Ersig
Journal:  Comput Inform Nurs       Date:  2012-10       Impact factor: 1.985

Review 4.  Data mining in healthcare and biomedicine: a survey of the literature.

Authors:  Illhoi Yoo; Patricia Alafaireet; Miroslav Marinov; Keila Pena-Hernandez; Rajitha Gopidi; Jia-Fu Chang; Lei Hua
Journal:  J Med Syst       Date:  2011-05-03       Impact factor: 4.460

5.  Data mining of mental health issues of non-bone marrow donor siblings.

Authors:  Morihito Takita; Yuji Tanaka; Yuko Kodama; Naoko Murashige; Nobuyo Hatanaka; Yukiko Kishi; Tomoko Matsumura; Yukio Ohsawa; Masahiro Kami
Journal:  J Clin Bioinforma       Date:  2011-07-20

6.  Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor.

Authors:  Dipankar Sengupta; Meemansa Sood; Poorvika Vijayvargia; Sunil Hota; Pradeep K Naik
Journal:  Bioinformation       Date:  2013-06-29

7.  Patterns of health care utilization preceding a colorectal cancer diagnosis are strong predictors of dying quickly following diagnosis.

Authors:  Robin Urquhart; Grace Johnston; Mohamed Abdolell; Geoff A Porter
Journal:  BMC Palliat Care       Date:  2015-01-20       Impact factor: 3.234

  7 in total

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