Application of Probabilistic Techniques for the Development of a Prognosis Model of Stroke Using Epidemiological Studies

Alejandro Rodríguez-González, Giner Alor-Hernandez, Miguel Angel Mayer, Guillermo Cortes-Robles and Yuliana Perez-Gallardo
Additional contact information
Alejandro Rodríguez-González: Bioinformatics at Centre for Plant Biotechnology and Genomics UPM-INIA, Polytechnic University of Madrid, Madrid, Spain
Giner Alor-Hernandez: Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Orizaba, Veracruz, Mexico
Miguel Angel Mayer: Research Programme on Biomedical Informatics (GRIB), IMIM-Universitat Pompeu Fabra, Barcelona, Spain
Guillermo Cortes-Robles: Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Orizaba, Veracruz, Mexico
Yuliana Perez-Gallardo: Computer Science Department, University Carlos III of Madrid, Orizaba, Veracruz, Spain

International Journal of Decision Support System Technology (IJDSST), 2013, vol. 5, issue 4, 34-58

Abstract: Automated medical diagnosis systems based on knowledge-oriented descriptions have gained momentum with the emergence of recent artificial intelligence techniques. The objective of this paper is to propose a design of a probabilistic model for the prevention of stroke based on the most outstanding risk factors associated with this pathology. The authors gather probabilistic technologies to develop a new clinical support decision-making model. This development is part of a future system that aims to improve health-quality and prevent strokes. The Naïve Bayes model is proposed to calculate the probability of suffering a stroke in the future, based on epidemiological data. Due to a new design, the model is capable to determine the probability of suffering a stroke given some risk factors. The proposed model allows to calculate the final probability of suffering a specific disease for the preventive prognosis of the stroke based on risk factors. Our model enables query the probability of suffering a stroke giving as parameter the presence or absence of a specific indication, also setting if the indication can take several values with its presence, degree or value. With the obtained results the physician will be able to promote patients healthy living habits in order to prevent future stroke events.

Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/ijdsst.2013100103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:5:y:2013:i:4:p:34-58

Access Statistics for this article

International Journal of Decision Support System Technology (IJDSST) is currently edited by Shaofeng Liu

More articles in International Journal of Decision Support System Technology (IJDSST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().