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

Bekzhan Darmeshov, Vasilios Zarikas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings of the Future Technologies Conference, FTC 2019 Volume 1
EditorsKohei Arai, Rahul Bhatia, Supriya Kapoor
PublisherSpringer
Pages124-143
Number of pages20
ISBN (Print)9783030325190
DOIs
Publication statusPublished - Jan 1 2020
Event4th Future Technologies Conference, FTC 2019 - San Francisco, United States
Duration: Oct 24 2019Oct 25 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1069
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th Future Technologies Conference, FTC 2019
CountryUnited States
CitySan Francisco
Period10/24/1910/25/19

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Keywords

  • Bacteraemia
  • Bayesian networks
  • Cancer
  • Expert model
  • Neutropenia

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Darmeshov, B., & Zarikas, V. (2020). Efficient Bayesian Expert Models for Fever in Neutropenia and Fever in Neutropenia with Bacteremia. In K. Arai, R. Bhatia, & S. Kapoor (Eds.), Proceedings of the Future Technologies Conference, FTC 2019 Volume 1 (pp. 124-143). (Advances in Intelligent Systems and Computing; Vol. 1069). Springer. https://doi.org/10.1007/978-3-030-32520-6_11