Cancer epidemiology of small communities: Using a novel approach to detecting clusters

E. Kordysh, A. Bolotin, M. Barchana, R. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cancer cluster detection in small communities is an important but complicated field of cancer epidemiology, due to large statistical errors of both types associated with the detection. In this paper, authors show the use of a new approach to this problem. This approach is based on three complementary techniques. One is aimed at detection of the cluster, and two others are applied after cluster detection in order to confirm or reject the cluster. Included is application of the approach in small agricultural-industrial communities of the South of Israel. The approach reduces both types of statistical errors, increases the chance to detect a true clustering and enables a first step in the identification of the cause of a cluster detected.

Original languageEnglish
Title of host publicationMedical Data Analysis - 2nd International Symposium, ISMDA 2001, Proceedings
EditorsJose Crespo, Victor Maojo, Fernando Martin
PublisherSpringer Verlag
Pages126-132
Number of pages7
ISBN (Electronic)3540427341, 9783540427346
DOIs
StatePublished - 1 Jan 2001
Event2nd International Symposium on Medical Data Analysis, ISMDA 2001 - Madrid, Spain
Duration: 8 Oct 20019 Oct 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2199
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Symposium on Medical Data Analysis, ISMDA 2001
Country/TerritorySpain
CityMadrid
Period8/10/019/10/01

Keywords

  • Cancer epidemiology
  • Cluster analysis for medical applications
  • Small agricultural-industrial communities
  • Temporal pattern analysis

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