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A Nearest Neighbor Approach to Build a Readable Risk Score for Breast Cancer

  • Émilien GauthierEmail author
  • Laurent Brisson
  • Philippe Lenca
  • Stéphane Ragusa
Chapter
Part of the Annals of Information Systems book series (AOIS, volume 17)

Abstract

According to the World Health Organization, starting from 2010, cancer has become the leading cause of death worldwide. Prevention of major cancer localizations through a quantified assessment of risk factors is a major concern in order to decrease their impact in our society. Our objective is to test the performances of a modeling method that answers to needs and constraints of end users. In this article, we follow a data mining process to build a reliable assessment tool for primary breast cancer risk. A k-nearest-neighbor algorithm is used to compute a risk score for different profiles from a public database. We empirically show that it is possible to achieve the same performances as logistic regressions with less attributes and a more easily readable model. The process includes the intervention of a domain expert, during an offline step of the process, who helps to select one of the numerous model variations by combining at best, physician expectations and performances. A risk score made of four parameters: age, breast density, number of affected first degree relatives and breast biopsy, is chosen. Detection performance measured with the area under the ROC curve is 0.637. A graphical user interface is presented to show how users will interact with this risk score.

Keywords

Breast Cancer Breast Cancer Risk Receiver Operating Characteristic Curve Risk Score Breast Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Émilien Gauthier
    • 1
    • 2
    • 3
    Email author
  • Laurent Brisson
    • 2
    • 3
  • Philippe Lenca
    • 2
    • 3
  • Stéphane Ragusa
    • 1
  1. 1.Statlife companyInstitut Gustave RoussyVillejuif CedexFrance
  2. 2.UMR CNRS 6285 Lab-STICCInstitut Telecom, Telecom BretagneBrest Cedex 3France
  3. 3.Université Européenne de BretagneBretagneFrance

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