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Data mining and healthcare informatics.

G R Hobbs1

  • 1Department of Mathematical Statistics, West Virginia School of Medicine, Morgantown, USA. ghobbs@stat.wvu.edu

American Journal of Health Behavior
|April 27, 2001
PubMed
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Data-mining offers valuable tools for researchers analyzing large datasets. This approach aids in developing predictive models and identifying associations, especially with the rise of online data collection.

Area of Science:

  • Data Science
  • Statistical Analysis
  • Health Informatics

Background:

  • The increasing availability of large datasets due to online data collection presents new opportunities.
  • Traditional statistical methods may be insufficient for exploring massive databases.

Purpose of the Study:

  • To introduce data-mining as a powerful technique for data exploration.
  • To highlight data-mining methods applicable to predictive modeling in healthcare research.

Main Methods:

  • A comprehensive review of data-mining concepts and methodologies.
  • Focus on data-mining techniques suitable for building predictive models.

Main Results:

  • Data-mining proves effective for researchers working with extensive information.

Related Experiment Videos

  • Demonstrates the utility of data-mining in extracting insights from large-scale data.

    • Conclusions:

    • Massive databases are now accessible to healthcare researchers.
    • Data-mining provides unique opportunities for developing prediction models and establishing associations.