Pattern mining for outbreak discovery preparedness

Zalizah Awang Long, Abdul Razak Hamdan, Azuraliza Abu Bakar, Mazrura Sahani

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Today, the objective of public health surveillance system is to reduce the impact of outbreaks by enabling appropriate intervention. Commonly used techniques are based on the changes or aberration in health events when compared with normal history to detect an outbreak. The main problem encountered in outbreaks is high rates of false alarm. High false alarm rates can lead to unnecessary interventions, and falsely detected outbreaks will lead to costly investigation. In this chapter, the authors review data mining techniques focusing on frequent and outlier mining to develop generic outbreak detection process model, named as "Frequent-outlier" model. The process model was tested against the real dengue dataset obtained from FSK, UKM, and also tested on the synthetic respiratory dataset obtained from AUTON LAB. The ROC was run to analyze the overall performance of "frequent-outlier" with CUSUM and Moving Average (MA). The results were promising and were evaluated using detection rate, false positive rate, and overall performance. An important outcome of this study is the knowledge rules derived from the notification of the outbreak cases to be used in counter measure assessment for outbreak preparedness.

Original languageEnglish
Title of host publicationMedical Applications of Intelligent Data Analysis: Research Advancements
PublisherIGI Global
Pages125-137
Number of pages13
ISBN (Print)9781466618039
DOIs
Publication statusPublished - 2012

Fingerprint

Frequency shift keying
Public health
Aberrations
Data mining
Health

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Long, Z. A., Hamdan, A. R., Abu Bakar, A., & Sahani, M. (2012). Pattern mining for outbreak discovery preparedness. In Medical Applications of Intelligent Data Analysis: Research Advancements (pp. 125-137). IGI Global. https://doi.org/10.4018/978-1-4666-1803-9.ch008

Pattern mining for outbreak discovery preparedness. / Long, Zalizah Awang; Hamdan, Abdul Razak; Abu Bakar, Azuraliza; Sahani, Mazrura.

Medical Applications of Intelligent Data Analysis: Research Advancements. IGI Global, 2012. p. 125-137.

Research output: Chapter in Book/Report/Conference proceedingChapter

Long, ZA, Hamdan, AR, Abu Bakar, A & Sahani, M 2012, Pattern mining for outbreak discovery preparedness. in Medical Applications of Intelligent Data Analysis: Research Advancements. IGI Global, pp. 125-137. https://doi.org/10.4018/978-1-4666-1803-9.ch008
Long ZA, Hamdan AR, Abu Bakar A, Sahani M. Pattern mining for outbreak discovery preparedness. In Medical Applications of Intelligent Data Analysis: Research Advancements. IGI Global. 2012. p. 125-137 https://doi.org/10.4018/978-1-4666-1803-9.ch008
Long, Zalizah Awang ; Hamdan, Abdul Razak ; Abu Bakar, Azuraliza ; Sahani, Mazrura. / Pattern mining for outbreak discovery preparedness. Medical Applications of Intelligent Data Analysis: Research Advancements. IGI Global, 2012. pp. 125-137
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