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Leif Groop

Leif Groop

Principal investigator

Leif Groop

A Bayesian Network for Probabilistic Reasoning and Imputation of Missing Risk Factors in Type 2 Diabetes

Author

  • Francesco Sambo
  • Andrea Facchinetti
  • Liisa Hakaste
  • Jasmina Kravic
  • Barbara Di Camillo
  • Giuseppe Fico
  • Jaakko Tuomilehto
  • Leif Groop
  • Rafael Gabriel
  • Tuomi Tiinamaija
  • Claudio Cobelli

Summary, in English

We propose a novel Bayesian network tool to model the probabilistic relations between a set of type 2 diabetes risk factors. The tool can be used for probabilistic reasoning and for imputation of missing values among risk factors. The Bayesian network is learnt from a joint training set of three European population studies. Tested on an independent patient set, the network is shown to be competitive with both a standard imputation tool and a widely used risk score for type 2 diabetes, providing in addition a richer description of the interdependencies between diabetes risk factors.

Department/s

  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence of Diabetes Research in Sweden

Publishing year

2015

Language

English

Pages

172-176

Publication/Series

Lecture Notes in Computer Science

Volume

9105

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Endocrinology and Diabetes

Keywords

  • values imputation
  • Missing
  • Probabilistic reasoning
  • Type 2 diabetes
  • Bayesian networks

Conference name

15th Conference on Artificial Intelligence in Medicine (AIME)

Conference date

2015-06-17 - 2015-06-20

Conference place

Univ Pavia, Pavia, Italy

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISSN: 1611-3349