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Submitted: 17 August 2012 Modified: 17 August 2012

Herdin Record #: R07-EVHRDC-08171201081265

DATA MINING IN HEALTHCARE: CURRENT APPLICATIONS AND ISSUES

Researchers

NameRole
1Ruben D. Canlas Jr. Author

Related Institutions

Institutions NameRole
Carnegie Mellon University Authors Affiliation

Publication Information

1.
Publication Type:
Thesis/Dissertations
Thesis Degree:
MS
Specialization:
IT
Publication Date:
August 2009

Objectives

The objectives of this paper are the following:
1. To enumerate current uses and highlight the importance of data mining in medicine and
public health,
2. To find data mining techniques used in other fields that may also be applied in the
health sector.
3. To identify issues and challenges in data mining as applied to the medical practise.
4. To outline some recommendations for discovering knowledge in electronic databases
through data mining.

Abstract

The successful application of data mining in highly visible fields like e-business, marketing
and retail have led to the popularity of its use in knowledge discovery in databases (KDD) in
other industries and sectors. Among these sectors that are just discovering data mining are the
fields of medicine and public health.
This research paper provides a survey of current techniques of KDD, using data mining tools
for healthcare and public health. It also discusses critical issues and challenges associated
with data mining and healthcare in general.
The research found a growing number of data mining applications, including analysis of
health care centers for better health policy-making, detection of disease outbreaks and preventable
hospital deaths, and detection of fraudulent insurance claims.