Automatic Diagnosis of Particular Diseases Using a Fuzzy-Neural Approach

S. A. Monadjemi; P. Moallem

doi:10.15866/irea.v6i1.15143

Automatic Diagnosis of Particular Diseases Using a Fuzzy-Neural Approach

S. A. Monadjemi^(1*), P. Moallem⁽²⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irea.v6i1.15143

Abstract

Automatic diagnosis of diseases always has been of interest as an interdisciplinary study amongst computer and medical science researchers. In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system. Employing ETM diseases as the case study, system eventually gets through the 97.5% of correct detection of abnormal cases.
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Keywords

Artificial Neural Networks; Fuzzy Logic; Medical Diagnosis; Symptoms; Fuzzification

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References

J. G. Wolff, Medical Diagnosis as Pattern Recognition in a Framework of Information Compression by Multiple Alignment, Unification and Search, Decision Support Systems, Vol 42, n 2, pp 608-625, 2006.

K. R. Sasikala, M. Petrou, Fuzzy Classification with a GIS as an Aid to Decision Making, Advances in remote sensing, vol. 4, n 4, pp. 97-105 1996.

F. Steimann, K. P. Adlassnig, Fuzzy Medical Diagnosis, MSc Thesis, Wien University, 2005.

T. Zrimec and I. Kononenko, Feasibility analysis of machine learning in medical diagnosis from aura images, In proceedings of the KIRLIONICS-98 Conference, Saint-Petersburg, Russia, 1998.

A. Pomi, F. Olivera, Context-sensitive auto associative memories as expert systems in medical diagnosis, BMC Medical Informatics and Decision Making, Vol 6, n 39, 2006.

L A. Zadeh, Biological application of the Theory of Fuzzy sets and System, In Proceedings of the first Biocybernetics of the Central Nervous System, 1969.

Wiser system, http://wiser.nlm.nih.gov/about.html.

MedWeaver medical software system, Retrieved from http://www.ovid.com/site/pdf/medweaverfactsheet.pdf ,2006.

R. Fuller, Neural Fuzzy System, (Abo Akademi University, 1995).

R. Schalkof, Artificial Neural Networks (Mc Graw Hill, 1994).

N. Salim, Medical Diagnosis Using Neural Networks, MSc Thesis, Faculty of Information Technology, Universiti Utara Malaysia, Sintok, Kedah, 2004.

S. Weigand, A. Huberman, and D. E. Rumelhart, Predicting the future: a connectionist approach, International Journal of Neural Systems, Vol 1, n 1, pp 195-220, 1990.

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