Neural Network Analysis of Crystalluria Content to Predict Urinary Stone Type.
Raed M AlmannieAbdullah K AlsufyaniAbdullah U AlturkiMana AlmuhaidebSaleh BinsalehAbdulaziz M AlthunayanMohammed A AlomarKhalid M AlbarraqFahad A AlyamiPublished in: Research and reports in urology (2021)
The predictive algorithm developed in the present study may be used with a patient's clinical parameters to predict the stone type. This approach predicts the stone types associated with certain patient characteristics with a high sensitivity and specificity, indicating that the models may be a valuable clinical tool in the diagnosis, management, and monitoring of stone diseases.