Stammdaten

Evaluation of Bayesian classifiers in asthma exacerbation prediction after medication discontinuation
Untertitel:
Kurzfassung:

Objective:  The achievement of the optimal control of the disease is of cardinal importance in asthma treatment. As the control of the disease is sustained the medication should be gradually reduced and then stopped. Nevertheless, the discontinuation of asthma medication may lead to loss of disease control and eventually to an exacerbation of the disease. The goal of this paper is to examine the performance of Bayesian network classifiers in predicting asthma exacerbation based on several patient’s parameters such as objective measurements and medical history data.

Results:  In this study several Bayesian network classifiers are presented and evaluated. It is shown that the proposed semi-naive network classifier with the use of Backward Sequential Elimination and Joining algorithm is able to predict if a patient will have an exacerbation of the disease after his last assessment with 93.84% accuracy and 90.9% sensitivity. In addition, the resulting structure and the conditional probability tables give a clear view of the probabilistic relationships between the used factors. This network may help the clinicians to identify the patients who are at high risk of having an exacerbation after stopping the medication and to confirm which factors are the most important.

Keywords:  Bayesian classifiers, Semi-Naive Bayes classifier, Asthma exacerbation, Prediction



Schlagworte:
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Art der Veröffentlichung Online Publikation
Erschienen in: BMC Res Notes
BMC Res Notes
zur Publikation
 ( BioMed Central; D. Krüger )
Erscheinungdatum: 05.08.2018
Titel der Serie: -
Bandnummer: 11
Heftnummer: 522
Erstveröffentlichung: Ja
Version: -
Seite: S. 1 - 6

Identifikatoren

ISBN: -
ISSN: -
DOI: -
AC-Nummer: -
Homepage: https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-018-3621-1
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Statistik
Universitätsstraße 65-67
9020  Klagenfurt am Wörthersee
Österreich
zur Organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 106007 - Biostatistik
  • 302 - Klinische Medizin
Forschungscluster Kein Forschungscluster ausgewählt
Zitationsindex
  • n.a.
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Environmental Monitoring and Risk Evaluation

Kooperationen

Organisation Adresse
Democritus University of Thrace
University Campus,
69100   Komotini
Griechenland
University Campus,
GR - 69100  Komotini

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