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Article type: Research Article
Authors: Mazzone, P.a | Fortuna, L.b | Arena, P.b; * | Pisani, R.c
Affiliations: [a] Department of Neurosurgery, Galliera Hospitals, Genova, Italy | [b] Dipartimento Elettrico, Elettronico e Sistemistico, University of Catania, Catania, Italy | [c] Department of Neurosurgery, Galliera Hospitals, Genova, Italy
Correspondence: [*] Corresponding author: Dr. Paolo Arena, Ph.D., Dipartimento Elettrico, Elettronico e Sistemistico, University of Catania, Viale A. Doria, 6, 95125 Catania, Italy. Tel.: +39 95 339 535; Fax: +39 95 330 793; E-mail: parena@dees.unict.it.
Abstract: The cerebrospinal fluid (CSF) pressure patterns have been reported as one of the most relevant indexes for the diagnosis and treatment of idiopathic normal-pressure hydrocephalus (INPH). Forty consecutive patients coming from our observations with the classic Hakim’s triad underwent continuous CSF pressure monitoring via lumbar puncture for at least 12 hours. Twenty-eight patients were diagnosed as having INPH and underwent CSF shunt. A multi-layer neural network (perceptron) was employed to study the pressure patterns in order to try an alternative classification to the “expert” neurosurgeon one. Differences between expert and neural network classifications were indeed observed. Such differences may depend on the small group studied or on the inadequacy of CFS pressure patterns in correctly individuating those INPH patients who benefit from shunt surgery. The authors think that neural network processing of INPH could add relevant information to select the “responder” patients to surgery: in fact neural networks represent a powerful methodology for aiding the expert to select the proper choice on the basis of “what learnt” by the networks themselves.
Keywords: Multi-layer neural network, classification, autoassociation, idiopathic normal-pressure hydrocephalus (INPH), cerebrospinal fluid (CSF) pressure
DOI: 10.3233/THC-1996-4404
Journal: Technology and Health Care, vol. 4, no. 4, pp. 393-401, 1996
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