Estimating the health-related quality of life of kidney stone patients: initial results from the Wisconsin Stone Quality of Life Machine-Learning Algorithm (WISQOL-MLA).
David-Dan NguyenJack W LuoXing Han LuSeth K BechisRoger L SurStephen Y NakadaJodi A AntonelliNecole M StreeperSri SivalingamDavis P ViprakasitTimothy D AverchJaime LandmanThomas ChiVernon M PaisBen H ChewVincent G BirdSero AndonianNoah E CanvasserJonathan D HarperKristina L PennistonNaeem BhojaniPublished in: BJU international (2020)
Harnessing the power of the WISQOL questionnaire, our initial results indicate that the WISQOL-MLA can adequately predict a stone patient's HRQoL from readily available clinical information. The algorithm adequately relies on relevant clinical factors to make its HRQoL predictions. Future improvements to the model are needed for direct clinical applications.