Embedded system for diagnosing dysfunctions in the lower urinary tract

Authors:
David Gil;Antonio Soriano;Daniel Ruiz;C. Alberto Montejo
Affiliations:
University of Alicante, Spain;University of Alicante, Spain;University of Alicante, Spain;University of Alicante, Spain
Venue:
Proceedings of the 2007 ACM symposium on Applied computing
Year:
2007

Citing 2
Cited 1

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Review: Using support vector machines in diagnoses of urological dysfunctions

Expert Systems with Applications: An International Journal

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Abstract

A diagnosis is probably one of the most demanding tasks in medicine. The applications related to diagnose comprise medical and scientific tasks. This paper shows the development of an embedded system for medical diagnosis using self organizing artificial neural networks. It is proposed in order to classify/predict the dysfunctions of the lower urinary tract with ubiquitous and mobility features. This system is meant to help the urologists in obtaining swiftly and accurately an automatic diagnosis for complex multi-variable systems, and to avoid painful and costly medical treatments. The technology opted to implement these devices is Field Programmable Gate Arrays (FPGA) since there are hardware and software design excellent tools. The clinical study has been carried out using the medical reports of patients with dysfunctions in the lower urinary tract. The system is able to distinguish (and classify) the most relevant dysfunctions of the lower urinary tract.