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Implementation of an Expert System to Diagnose Spinal Diseases

Miguel F. Rocha1, Leonardo Orozco1,2,3, M. Rosario Osnaya1,2,3 , Darío R.1,2,3, Rafael Navarrete1,2,3, M. I. Rocha G.1,2,3, and E. Andrade1,2,3
1.ESIME, Instituto Politécnico Nacional, U.P. A.L. Mateos, G. A. Madero, México D.F. 07738, México
2.Grupo de Fenómenos Ondulatorios, Departamento de Ingeniería Electrónica, Universidad Politécnica de Valencia, España
3.Instituto de Física, Universidad Nacional Autónoma de México
Abstract—Sometimes medical human specialists may be affected by fatigue which may impact in their professional response. The spine consists of 26 bones called vertebrae, the vertebrae protect the spinal cord and allowed to stand and remain in an upright position. The objective of this paper is to implement an Expert System (ES) to diagnose spinal diseases by means of Morphological Hetero-Associative Memories and compare it with other approaches proposed previously in the literature. The implemented expert system based on Morphological Hetero-Associative Memories is able to diagnose normal status, disk hernia or spondylolisthesis, with a degree of reliability of up to 87.74% for a given TR of 100%.

Index Terms—expert system, morphological hetero-associative memories

Cite: Miguel F. Rocha, Leonardo Orozco, M. Rosario Osnaya, Darío R., Rafael Navarrete, M. I. Rocha G., and E. Andrade, "Implementation of an Expert System to Diagnose Spinal Diseases," Journal of Industrial and Intelligent Information, Vol. 3, No. 1, pp. 65-68, March 2015. doi: 10.12720/jiii.3.1.65-68
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