DIAGNOSIS OF DEMENTIA AND ITS PATHOLOGIES USING BAYESIAN BELIEF NETWORKS

Julie Cowie, Lloyd Oteniya, Richard Coles

2006

Abstract

The use of artificial intelligence techniques in medical decision support systems is becoming more commonplace. By incorporating a method to represent expert knowledge, such systems can aid the user in aspects such as disease diagnosis and treatment planning. This paper reports on the first part of a project addressing the diagnosis of individuals with dementia. We discuss two systems: DemNet and PathNet; developed to aid accurate diagnosis both of the presence of dementia, and the pathology of the disease.

References

  1. Alzheimer's Society. (2005). Facts about dementia, Alzheimer's society, Dementia care and research. Retrieved January 20, 2006, from http://www.alzheimers.org.uk/Facts_about_dementia/ How_dementia_progresses/index.htm
  2. de Toro F.J., Ros, E., Ortega, J. (2003). Non-invasive Atrial Disease Diagnosis Using Decision Rules: A Multi-objective Optimisation Approach. In Proceedings of 2nd International EMO Conference, pages 638-647, Faro, Portugal, April 2003. SpringerVerlag.
  3. Dybowski, R., Weller, P., Chang, R., Gant, V. (1996). Prediction of outcome in the critically ill using an artificial neural network synthesised by a genetic algorithm. The Lancet, 9009(347): 1146-1150.
  4. García-Pérez, E., Violante A., Cervantes-Pérez, F. (1998). Using neural networks for differential diagnosis of Alzheimer disease and vascular dementia. Expert Systems with Applications, 1-2(14): 219-225.
  5. Gill, C.J., Sabin, L., Schmid, C.H. (2005). Why clinicians are natural Bayesians. British Medical Journal 330: 1080 - 1083
  6. Kaplan, B. (2001). Evaluating informatics applications - clinical decision support systems literature review. International Journal of Medical Informatics, 1(64): 15-37.
  7. Mani, S., Shankle, W.R., Pazzani, M.J., Smyth, P. Dick, M.B. (1997). Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. J. of American Medical Informatics Assoc., 1(12), 875-880.
  8. Oteniya, L., Coles. R., Cowie, J. (2005). DemNet: A Clinical Decision Support System to Aid the Diagnosis of Dementia. In Proceedings of the HealthCare Computing conference, Harrogate, U.K., 289-297, March 2005.
  9. Oteniya, L., Coles, R., Cowie, J. (2006). Constructing a Bayesian belief network to support dementia diagnosis using expert knowledge. In progress.
  10. Werner, J.C., Fogarty, T. (2001). Genetic programming applied to Collagen disease and thrombosis. In Proceedings of The European Conference on Principles and Practice of Knowledge Discovery in Databases, 14-20, Germany.
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Paper Citation


in Harvard Style

Cowie J., Oteniya L. and Coles R. (2006). DIAGNOSIS OF DEMENTIA AND ITS PATHOLOGIES USING BAYESIAN BELIEF NETWORKS . In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-972-8865-42-9, pages 291-295. DOI: 10.5220/0002441802910295


in Bibtex Style

@conference{iceis06,
author={Julie Cowie and Lloyd Oteniya and Richard Coles},
title={DIAGNOSIS OF DEMENTIA AND ITS PATHOLOGIES USING BAYESIAN BELIEF NETWORKS},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2006},
pages={291-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002441802910295},
isbn={978-972-8865-42-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - DIAGNOSIS OF DEMENTIA AND ITS PATHOLOGIES USING BAYESIAN BELIEF NETWORKS
SN - 978-972-8865-42-9
AU - Cowie J.
AU - Oteniya L.
AU - Coles R.
PY - 2006
SP - 291
EP - 295
DO - 10.5220/0002441802910295