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Efficient Bayesian Expert Models for Fever in Neutropenia and Fever in Neutropenia with Bacteremia

  • Bekzhan Darmeshov
  • Vasilios ZarikasEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1069)

Abstract

Bayesian expert models are very efficient solutions since they can encapsulate in a mathematical consistent way, certain and uncertain knowledge, as well as preferences strategies and policies. Furthermore, the Bayesian modelling framework is the only one that can inference about causal connections and suggest the structure of a reasonable probabilistic model from historic data. Two novel expert models have been developed for a medical issue concerning diagnosis of fever in neutropenia or fever in neutropenia with bacteremia. Supervised and unsupervised learning was used to construct these two the expert models. The best one of them exhibited 93% precision of prediction.

Keywords

Bayesian networks Expert model Cancer Neutropenia Bacteraemia 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Mechanical and Aerospace Engineering Department, School of EngineeringNazarbayev UniversityNur-Sultan (Astana)Kazakhstan
  2. 2.School of EngineeringNazarbayev UniversityNur-Sultan (Astana)Kazakhstan
  3. 3.Theory Division, General DepartmentUniversity of ThessalyVolosGreece

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