Integrated mining for cancer incidence factors from healthcare data

  • Authors:
  • Xiaolong Zhang;Tetsuo Narita

  • Affiliations:
  • School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China;ISV Solutions, IBM-Japan Application Solution Co., Ltd., Kanagawa, Japan

  • Venue:
  • AM'03 Proceedings of the Second international conference on Active Mining
  • Year:
  • 2003

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Abstract

This paper describes how data mining is being used to identify primary factors of cancer incidences and living habits of cancer patients from a set of health and living habit questionnaires. Decision tree, radial basis function and back propagation neural network have been employed in this case study. Decision tree classification uncovers the primary factors of cancer patients from rules. Radial basis function method has advantages in comparing the living habits between a group of cancer patients and a group of healthy people. Back propagation neural network contributes to elicit the important factors of cancer incidences. This case study provides a useful data mining template for characteristics identification in healthcare and other areas.