Modeling of Neuropathic Bladder Lesions Diagnosis Using Neural Network Algorithm.

Abstract

The urinary bladder is probably the only visceral smooth-muscle organ that is under complete voluntary control from the cerebral cortex. Normal bladder function requires interaction of sensory and motor components of both the somatic and autonomic nervous system. Recent advances in the understanding of neural pathways and neurotransmitters have shown that most levels of the nervous system are involved in the regulation of voiding function. Therefore

many neuralgic diseases causes changes in the bladder function [1]. In this paper, Number of patients selected from Ibn-Alkiff hospital (for treatment and

rehabilitation of Spinal cord injuries), in Baghdad, who were referred to the urology department for complains of some urinary symptoms, and examined by cystometry in the urology out patient and/or inpatient department. These cases were selected randomly who already consult these departments and were

followed up and managed by the expert urosurgeons. They were adults complaining of general neuropathic bladder disorder symptoms like frequency, urgency, dysuria, urinary incontinence and were diagnosed as having neuropathic bladder disease, whether: Upper motor neuropathic bladder lesions. Lower motor neuropathic bladder lesions. And finally they were examined by cystometry. The collections of data from patients were about: Accommodation (compliance).

1. Bladder capacity.
2. Contractility.
3. Sensation.
4. Voluntary control.

These data with the final definition diagnosis about the neuropathic bladder lesion were processed to 3- layers Neural Network algorithm that was constructed in a matlab computer package. Consequently after all data processing, the neural network model was tested by its capability of processing an already diagnosed neuropathic bladder case and its accuracy in explaining the real neurological bladder behavior of that selected patient