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Prediction of upper urinary tract calculi using an artificial neural network

Tanthanuch, M.; Tanthanuch, S.

Journal of the Medical Association of Thailand 87(5): 515-518

2004

ISSN/ISBN: 0125-2208
PMID: 15222521
Document Number: 2430
Objectives : To evaluate the possibility of using an artificial neural network (ANN) in upper urinary tract calculi prediction. Material and Method., Data of 168 upper urinary tract calculi patients treated in the Division of Urology, Department of surgery, Songklanagarind Hospital from January 1997 to December 2000 were reviewed and classified into 6 catagories and 20 characteristics. 100 items were used in training and 68 in resting for an ANN designed with 3 layers: 20 nodes for an input layer, 5 nodes for a hidden layer and a node for the output layer. Results : Output data between 0-0.38 indicate free of calculi, 0.65-1 indicate prone to have calculi, 0.38-0.65 indicate probable calculi and further need investigation. Conclusion : An ANN with error back-propagation training can he used in diagnosing the presence of upper urinary tract calculi. The accuracy of prediction depends on a previous history of calculi, nephrocalcinosis, 24 hour urine assay for citrate and urine culture.

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Prediction of upper urinary tract calculi using an artificial neural network

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